Publications by authors named "Kefyalew Addis Alene"

41 Publications

Risk factors for COVID-19 infection, disease severity and related deaths in Africa: a systematic review.

BMJ Open 2021 02 18;11(2):e044618. Epub 2021 Feb 18.

Department of Epidemiology and Biostatistics, University of Gondar, Gondar, Ethiopia.

Objective: The aim of this study was to provide a comprehensive evidence on risk factors for transmission, disease severity and COVID-19 related deaths in Africa.

Design: A systematic review has been conducted to synthesise existing evidence on risk factors affecting COVID-19 outcomes across Africa.

Data Sources: Data were systematically searched from MEDLINE, Scopus, MedRxiv and BioRxiv.

Eligibility Criteria: Studies for review were included if they were published in English and reported at least one risk factor and/or one health outcome. We included all relevant literature published up until 11 August 2020.

Data Extraction And Synthesis: We performed a systematic narrative synthesis to describe the available studies for each outcome. Data were extracted using a standardised Joanna Briggs Institute data extraction form.

Results: Fifteen articles met the inclusion criteria of which four were exclusively on Africa and the remaining 11 papers had a global focus with some data from Africa. Higher rates of infection in Africa are associated with high population density, urbanisation, transport connectivity, high volume of tourism and international trade, and high level of economic and political openness. Limited or poor access to healthcare are also associated with higher COVID-19 infection rates. Older people and individuals with chronic conditions such as HIV, tuberculosis and anaemia experience severe forms COVID-19 leading to hospitalisation and death. Similarly, high burden of chronic obstructive pulmonary disease, high prevalence of tobacco consumption and low levels of expenditure on health and low levels of global health security score contribute to COVID-19 related deaths.

Conclusions: Demographic, institutional, ecological, health system and politico-economic factors influenced the spectrum of COVID-19 infection, severity and death. We recommend multidisciplinary and integrated approaches to mitigate the identified factors and strengthen effective prevention strategies.
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http://dx.doi.org/10.1136/bmjopen-2020-044618DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7896374PMC
February 2021

COVID-19 in Ethiopia: a geospatial analysis of vulnerability to infection, case severity and death.

BMJ Open 2021 02 18;11(2):e044606. Epub 2021 Feb 18.

University of Canberra, Canberra, Australian Capital Territory, Australia.

Background: COVID-19 has caused a global public health crisis affecting most countries, including Ethiopia, in various ways. This study maps the vulnerability to infection, case severity and likelihood of death from COVID-19 in Ethiopia.

Methods: Thirty-eight potential indicators of vulnerability to COVID-19 infection, case severity and likelihood of death, identified based on a literature review and the availability of nationally representative data at a low geographic scale, were assembled from multiple sources for geospatial analysis. Geospatial analysis techniques were applied to produce maps showing the vulnerability to infection, case severity and likelihood of death in Ethiopia at a spatial resolution of 1 km×1 km.

Results: This study showed that vulnerability to COVID-19 infection is likely to be high across most parts of Ethiopia, particularly in the Somali, Afar, Amhara, Oromia and Tigray regions. The number of severe cases of COVID-19 infection requiring hospitalisation and intensive care unit admission is likely to be high across Amhara, most parts of Oromia and some parts of the Southern Nations, Nationalities and Peoples' Region. The risk of COVID-19-related death is high in the country's border regions, where public health preparedness for responding to COVID-19 is limited.

Conclusion: This study revealed geographical differences in vulnerability to infection, case severity and likelihood of death from COVID-19 in Ethiopia. The study offers maps that can guide the targeted interventions necessary to contain the spread of COVID-19 in Ethiopia.
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http://dx.doi.org/10.1136/bmjopen-2020-044606DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7896372PMC
February 2021

Improving Influenza Vaccination in Children With Comorbidities: A Systematic Review.

Pediatrics 2021 Mar 8;147(3). Epub 2021 Feb 8.

Wesfarmers Centre of Vaccines and Infectious Diseases, Telethon Kids Institute, Western Australia, Australia.

Context: Children with medical comorbidities are at greater risk for severe influenza and poorer clinical outcomes. Despite recommendations and funding, influenza vaccine coverage remains inadequate in these children.

Objective: We aimed to systematically review literature assessing interventions targeting influenza vaccine coverage in children with comorbidities and assess the impact on influenza vaccine coverage.

Data Sources: PubMed, Scopus, Embase, Cumulative Index to Nursing and Allied Health Literature, Cochrane Central Register of Controlled Trials, Allied and Complementary Medicine Database, and Web of Science databases were searched.

Study Selection: Interventions targeting influenza vaccine coverage in children with medical comorbidities.

Data Extraction: Two reviewers independently screened articles, extracting studies' methods, interventions, settings, populations, and results. Four reviewers independently assessed risk of bias.

Results: From 961 screened articles, 35 met inclusion criteria. Published studies revealed that influenza vaccine coverage was significantly improved through vaccination reminders and education directed at either patients' parents or providers, as well as by vaccination-related clinic process changes. Interventions improved influenza vaccine coverage by an average 60%, but no significant differences between intervention types were detected. Significant bias and study heterogeneity were also identified, limiting confidence in this effect estimate.

Limitations: A high risk of bias and overall low quality of evidence limited our capacity to assess intervention types and methods.

Conclusions: Interventions were shown to consistently improve influenza vaccine coverage; however, no significant differences in coverage between different intervention types were observed. Future well-designed studies evaluating the effectiveness of different intervention are required to inform future optimal interventions.
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http://dx.doi.org/10.1542/peds.2020-1433DOI Listing
March 2021

Poor treatment outcomes of children on highly active antiretroviral therapy: protocol for a systematic review and meta-analysis.

BMJ Open 2020 12 29;10(12):e040161. Epub 2020 Dec 29.

Faculty of Health Sciences, Curtin University, Bentley Campus, Perth, Western Australia, Australia.

Introduction: While access to highly active antiretroviral therapy (HAART) for children with HIV has expanded and the use of HAART has substantially reduced the morbidity and mortality of children due to HIV, poor treatment outcomes among children with HIV are still a major public health problem globally. The aim of this systematic review and meta-analysis is to quantify treatment outcomes among children with HIV.

Methods And Analysis: Systematic searches will be conducted in three electronic databases (PubMed, SCOPUS and Web of Science) for recent studies published from 01 Jan 2000 up to 28 October 2020, without geographical restriction. The primary outcomes of the study will be poor treatment outcomes, which include death, treatment failure and loss to follow-up. We will include quantitative studies that report treatment outcomes among children under the age of 18 years with HIV. Studies will be excluded if they are case report, case series, conducted among adults only or do not provide data on treatment outcomes for children. Two researchers will screen the titles and abstracts of all citations identified in our search, then review the full text of the remaining papers to identify those that meet the inclusion criteria. The Newcastle-Ottawa Scale will be used for quality assessment. A random-effects meta-analysis will be used to obtain pooled estimates of the proportion of poor treatment outcomes. The heterogeneity between studies will be checked visually by using forest plots and quantitatively measured by the index of heterogeneity (I). Pooled estimates of poor treatment outcomes will be calculated with a random-effects model. Subgroup analysis will be conducted by study settings, treatment regimen, comorbidity (such as tuberculosis), study period and HIV type (HIV-1 and HIV-2).

Ethics And Dissemination: Ethical approval will not be required for this study as it will be based on published papers. The final report of this review will be published in a peer-reviewed scientific journal.
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http://dx.doi.org/10.1136/bmjopen-2020-040161DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7778777PMC
December 2020

Impact of the COVID-19 Pandemic on Tuberculosis Control: An Overview.

Trop Med Infect Dis 2020 Jul 24;5(3). Epub 2020 Jul 24.

Faculty of Health Sciences, Curtin University, Bentley, WA 6102, Australia.

Throughout history, pandemics of viral infections such as HIV, Ebola and Influenza have disrupted health care systems, including the prevention and control of endemic diseases. Such disruption has resulted in an increased burden of endemic diseases in post-pandemic periods. The current coronavirus disease 2019 (COVID-19) pandemic could cause severe dysfunction in the prevention and control of tuberculosis (TB), the infectious disease that causes more deaths than any other, particularly in low- and middle-income countries where the burden of TB is high. The economic and health crisis created by the COVID-19 pandemic as well as the public health measures currently taken to stop the spread of the virus may have an impact on household TB transmission, treatment and diagnostic services, and TB prevention and control programs. Here, we provide an overview of the potential impact of COVID-19 on TB programs and disease burden, as well as possible strategies that could help to mitigate the impact.
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http://dx.doi.org/10.3390/tropicalmed5030123DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7558533PMC
July 2020

Treatment outcomes of patients with tuberculosis in war affected region of Khyber Pakhtunkhwa, Pakistan.

BMC Infect Dis 2020 Jul 1;20(1):463. Epub 2020 Jul 1.

Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, 210009, China.

Background: Globally, tuberculosis (TB) remains the leading cause of death from a single infectious disease. TB treatment outcome is an important indicator for the effectiveness of a national TB control program. This study aimed to assess treatment outcomes of TB patients and its determinants in Batkhela, Khyber Pakhtunkhwa, Pakistan.

Methods: A retrospective cohort study was designed using all TB patients who were enrolled at District Head Quarter (DHQ) Hospital Batkhela, Pakistan, from January 2011 to December 2014. A binary logistic regression models were used to identify factors associated with successful TB treatment outcomes defined as the sum of cure and completed treatment.

Results: A total of 515 TB patients were registered, of which 237 (46%) were males and 278 (53.98%) females. Of all patients, 234 (45.44%) were cured and 210 (40.77%) completed treatment. The overall treatment success rate was 444 (86.21%). Age 0-20 years (adjusted odds ratio, AOR = 3.47; 95% confidence interval, CI) = 1.54-7.81; P = 0.003), smear-positive pulmonary TB (AOR) = 3.58; 95% CI = 1.89-6.78; P = < 0.001), treatment category (AOR = 4.71; 95% CI = 1.17-18.97; P = 0.029), and year of enrollment 2012 (AOR = 6.26; 95% CI = 2.52-15.59; P = < 0.001) were significantly associated with successful treatment outcome.

Conclusions: The overall treatment success rate is satisfactory but still need to be improved to achieve the international targeted treatment outcome. Type of TB, age, treatment category, and year of enrollment were significantly associated with successful treatment outcomes.
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http://dx.doi.org/10.1186/s12879-020-05184-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7329461PMC
July 2020

Mapping tuberculosis prevalence in Ethiopia: protocol for a geospatial meta-analysis.

BMJ Open 2020 05 25;10(5):e034704. Epub 2020 May 25.

Wesfarmers Centre of Vaccines and Infectious Diseases, Telethon Kids Institute, Nedlands, Western Australia, Australia.

Introduction: Tuberculosis (TB), a major public health concern in Ethiopia, is distributed heterogeneously across the country. Mapping TB prevalence at national and subnational levels can provide information for designing and implementing control strategies. Data for spatial analysis can be obtained through systematic review of the literature, and spatial prediction can be done by meta-analysis of published data (geospatial meta-analysis). Geospatial meta-analysis can increase the power of spatial analytic models by making use of all available data. It can also provide a means for spatial prediction where new survey data in a given area are sparse or not available. In this report, we present a protocol for a geospatial meta-analysis to investigate the spatial patterns of TB prevalence in Ethiopia.

Methods And Analysis: To conduct this study, a national TB prevalence survey, supplemented with data from a systematic review of published reports, will be used as the source of TB prevalence data. Systematic searching will be conducted in PubMed, Scopus and Web of Science for studies published up to 15 April 2020 to identify all potential publications reporting TB prevalence in Ethiopia. Data for covariates for multivariable analysis will be obtained from different, readily available sources. Extracted TB survey and covariate data will be georeferenced to specific locations or the centroids of small administrative areas. A binomial logistic regression model will be fitted to TB prevalence data using both fixed covariate effects and random geostatistical effects based on the approach of model-based geostatistics. Markov Chain Monte Carlo simulation will be conducted to obtained posterior parameter estimations, including spatially predicted prevalence.

Ethics And Dissemination: Ethical approval will not be required for this study as it will be based on deidentified, aggregate published data. The final report of this review will be disseminated through publication in a peer-reviewed scientific journal and will also be presented at relevant conferences.
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http://dx.doi.org/10.1136/bmjopen-2019-034704DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7252965PMC
May 2020

Development of a risk score for prediction of poor treatment outcomes among patients with multidrug-resistant tuberculosis.

PLoS One 2020 3;15(1):e0227100. Epub 2020 Jan 3.

Faculty of Health Sciences, Curtin University, Perth, Western Australia, Australia.

Background: Treatment outcomes among patients treated for multidrug-resistant tuberculosis (MDR-TB) are often sub-optimal. Therefore, the early prediction of poor treatment outcomes may be useful in patient care, especially for clinicians when they have the ability to make treatment decisions or offer counselling or additional support to patients. The aim of this study was to develop a simple clinical risk score to predict poor treatment outcomes in patients with MDR-TB, using routinely collected data from two large countries in geographically distinct regions.

Methods: We used MDR-TB data collected from Hunan Chest Hospital, China and Gondar University Hospital, Ethiopia. The data were divided into derivation (n = 343; 60%) and validation groups (n = 227; 40%). A poor treatment outcome was defined as treatment failure, lost to follow up or death. A risk score for poor treatment outcomes was derived using a Cox proportional hazard model in the derivation group. The model was then validated in the validation group.

Results: The overall rate of poor treatment outcome was 39.5% (n = 225); 37.9% (n = 86) in the derivation group and 40.5% (n = 139) in the validation group. Three variables were identified as predictors of poor treatment outcomes, and each was assigned a number of points proportional to its regression coefficient. These predictors and their points were: 1) history of taking second-line TB treatment (2 points), 2) resistance to any fluoroquinolones (3 points), and 3) smear did not convert from positive to negative at two months (4 points). We summed these points to calculate the risk score for each patient; three risk groups were defined: low risk (0 to 2 points), medium risk (3 to 5 points), and high risk (6 to 9 points). In the derivation group, poor treatment outcomes were reported for these three groups as 14%, 27%, and 71%, respectively. The area under the receiver operating characteristic curve for the point system in the derivation group was 0.69 (95% CI 0.60 to 0.77) and was similar to that in the validation group (0.67; 95% CI 0.56 to 0.78; p = 0.82).

Conclusion: History of second-line TB treatment, resistance to any fluoroquinolones, and smear non-conversion at two months can be used to estimate the risk of poor treatment outcome in patients with MDR-TB with a moderate degree of accuracy (AUROC = 0.69).
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0227100PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6941813PMC
April 2020

Impact of multidrug-resistant tuberculosis and its medications on adverse maternal and perinatal outcomes: protocol for a systematic review and meta-analysis.

BMJ Open 2019 12 15;9(12):e034821. Epub 2019 Dec 15.

Agriculture and Environment, The University of Western Australia, Crawley, Western Australia, Australia

Introduction: Multidrug-resistant tuberculosis (MDR-TB) is a common public health problem affecting pregnant women. However, the impact of MDR-TB and its medication on pregnancy and perinatal outcomes has been poorly understood and inconsistently reported. Therefore, using the available literature, we aim to determine whether MDR-TB and its medications during pregnancy impact maternal and perinatal outcomes.

Methods And Analysis: This systematic review and meta-analysis will adhere to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Systematic searches will be conducted in PubMed, Scopus and Web of Science on 10 February 2020 for studies that reported adverse maternal and perinatal outcomes due to MDR-TB and/or its medication. The search will be performed without language and time restrictions. Adverse birth outcomes include miscarriage or abortion, stillbirth, preterm birth, low birth weight, small and large for gestational age, and neonatal death. Two independent reviewers will screen search records, extract data and assess the quality of the studies. The Newcastle-Ottawa Quality Assessment Scale will be used to assess the methodological quality of the included studies. In addition to a narrative synthesis, a random-effects meta-analysis will be conducted when sufficient data are available. I statistics will be used to assess the heterogeneity between studies.

Ethics And Dissemination: As it will be a systematic review and meta-analysis based on previously published evidence, there will be no requirement for ethical approval. Findings will be published in a peer-reviewed journal and will be presented at various conferences.
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http://dx.doi.org/10.1136/bmjopen-2019-034821DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6924852PMC
December 2019

Spatial patterns of tuberculosis and HIV co-infection in Ethiopia.

PLoS One 2019 5;14(12):e0226127. Epub 2019 Dec 5.

Faculty of Health Sciences, Curtin University, Perth, Western Australia, Australia.

Background: Tuberculosis (TB) and human immunodeficiency virus (HIV) are the leading causes of infectious-disease-related deaths in Ethiopia, but little is known about their spatial distribution across the country. The aim of this study was to investigate the spatial patterns of TB and HIV co-infection in Ethiopia at the district level.

Methods: We conducted an ecological study using TB and HIV data reported from all regions of Ethiopia through the national Health Management Information System (HMIS), between June 2015 and June 2017. Spatial clustering was assessed using Moran's I statistic and Getis-Ord statistic. Spatial binomial regression models were constructed separately for the prevalence of TB among people living with HIV and for the prevalence of HIV among TB patients, with and without spatial components using a Bayesian approach.

Results: A total of 1,830,880 HIV and 192,359 TB patients were included in the analysis. The prevalence of HIV among TB patients was 7.34%; hotspots were observed in districts located in Amhara, Afar, and Gambela regions, and cold spots were observed in Oromiya and Southern Nations, Nationalities, and People (SNNP) regions. The prevalence of TB among people living with HIV varied from 0.7% in Oromia region to 14.5% in Afar region. Hotspots of TB prevalence among people living with HIV were observed in districts located in Gambela, Afar, Somali, and Oromiya regions; whereas the cold spots were observed in districts located in Amhara and Tigray regions. The ecological-level factors associated with the prevalence of TB among people living with HIV were low wealth index (OR: 1.49; 95% CrI: 1.05, 2.05), low adult literacy rate (OR: 0.67; 95% CrI: 0.46, 0.94), and distance to an international border (OR: 0.61; 95% CrI: 0.40, 0.91). The factors associated with the prevalence of HIV among TB patients were poor health care access (OR: 0.76; 95% CrI: 0.59, 0.95), low wealth index (OR: 1.31; 95% CrI: 1.01, 1.67), and low adult literacy rate (OR: 1.37; 95% CrI: 1.03, 1.78).

Conclusion: Our study provides evidence for geographic clustering of TB/HIV co-infection in Ethiopia. Health care access, proximity to international borders, and demographic factors such as low wealth index and adult literacy were significantly associated with the prevalence of TB/HIV co-infection.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0226127PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6894814PMC
March 2020

Mapping 123 million neonatal, infant and child deaths between 2000 and 2017.

Authors:
Roy Burstein Nathaniel J Henry Michael L Collison Laurie B Marczak Amber Sligar Stefanie Watson Neal Marquez Mahdieh Abbasalizad-Farhangi Masoumeh Abbasi Foad Abd-Allah Amir Abdoli Mohammad Abdollahi Ibrahim Abdollahpour Rizwan Suliankatchi Abdulkader Michael R M Abrigo Dilaram Acharya Oladimeji M Adebayo Victor Adekanmbi Davoud Adham Mahdi Afshari Mohammad Aghaali Keivan Ahmadi Mehdi Ahmadi Ehsan Ahmadpour Rushdia Ahmed Chalachew Genet Akal Joshua O Akinyemi Fares Alahdab Noore Alam Genet Melak Alamene Kefyalew Addis Alene Mehran Alijanzadeh Cyrus Alinia Vahid Alipour Syed Mohamed Aljunid Mohammed J Almalki Hesham M Al-Mekhlafi Khalid Altirkawi Nelson Alvis-Guzman Adeladza Kofi Amegah Saeed Amini Arianna Maever Loreche Amit Zohreh Anbari Sofia Androudi Mina Anjomshoa Fereshteh Ansari Carl Abelardo T Antonio Jalal Arabloo Zohreh Arefi Olatunde Aremu Bahram Armoon Amit Arora Al Artaman Anvar Asadi Mehran Asadi-Aliabadi Amir Ashraf-Ganjouei Reza Assadi Bahar Ataeinia Sachin R Atre Beatriz Paulina Ayala Quintanilla Martin Amogre Ayanore Samad Azari Ebrahim Babaee Arefeh Babazadeh Alaa Badawi Soghra Bagheri Mojtaba Bagherzadeh Nafiseh Baheiraei Abbas Balouchi Aleksandra Barac Quique Bassat Bernhard T Baune Mohsen Bayati Neeraj Bedi Ettore Beghi Masoud Behzadifar Meysam Behzadifar Yared Belete Belay Brent Bell Michelle L Bell Dessalegn Ajema Berbada Robert S Bernstein Natalia V Bhattacharjee Suraj Bhattarai Zulfiqar A Bhutta Ali Bijani Somayeh Bohlouli Nicholas J K Breitborde Gabrielle Britton Annie J Browne Sharath Burugina Nagaraja Reinhard Busse Zahid A Butt Josip Car Rosario Cárdenas Carlos A Castañeda-Orjuela Ester Cerin Wagaye Fentahun Chanie Pranab Chatterjee Dinh-Toi Chu Cyrus Cooper Vera M Costa Koustuv Dalal Lalit Dandona Rakhi Dandona Farah Daoud Ahmad Daryani Rajat Das Gupta Ian Davis Nicole Davis Weaver Dragos Virgil Davitoiu Jan-Walter De Neve Feleke Mekonnen Demeke Gebre Teklemariam Demoz Kebede Deribe Rupak Desai Aniruddha Deshpande Hanna Demelash 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Niegia Garcia Goulart Nicholas Graetz Felix Greaves Manfred S Green Yuming Guo Arvin Haj-Mirzaian Arya Haj-Mirzaian Brian James Hall Samer Hamidi Hamidreza Haririan Josep Maria Haro Milad Hasankhani Edris Hasanpoor Amir Hasanzadeh Hadi Hassankhani Hamid Yimam Hassen Mohamed I Hegazy Delia Hendrie Fatemeh Heydarpour Thomas R Hird Chi Linh Hoang Gillian Hollerich Enayatollah Homaie Rad Mojtaba Hoseini-Ghahfarokhi Naznin Hossain Mostafa Hosseini Mehdi Hosseinzadeh Mihaela Hostiuc Sorin Hostiuc Mowafa Househ Mohamed Hsairi Olayinka Stephen Ilesanmi Mohammad Hasan Imani-Nasab Usman Iqbal Seyed Sina Naghibi Irvani Nazrul Islam Sheikh Mohammed Shariful Islam Mikk Jürisson Nader Jafari Balalami Amir Jalali Javad Javidnia Achala Upendra Jayatilleke Ensiyeh Jenabi John S Ji Yash B Jobanputra Kimberly Johnson Jost B Jonas Zahra Jorjoran Shushtari Jacek Jerzy Jozwiak Ali Kabir Amaha Kahsay Hamed Kalani Rohollah Kalhor Manoochehr Karami Surendra Karki Amir Kasaeian Nicholas J Kassebaum Peter Njenga 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Ballard Massenburg Pallab K Maulik Benjamin K Mayala Mohsen Mazidi Martin McKee Ravi Mehrotra Kala M Mehta Gebrekiros Gebremichael Meles Walter Mendoza Ritesh G Menezes Atte Meretoja Tuomo J Meretoja Tomislav Mestrovic Ted R Miller Molly K Miller-Petrie Edward J Mills George J Milne G K Mini Seyed Mostafa Mir Hamed Mirjalali Erkin M Mirrakhimov Efat Mohamadi Dara K Mohammad Aso Mohammad Darwesh Naser Mohammad Gholi Mezerji Ammas Siraj Mohammed Shafiu Mohammed Ali H Mokdad Mariam Molokhia Lorenzo Monasta Yoshan Moodley Mahmood Moosazadeh Ghobad Moradi Masoud Moradi Yousef Moradi Maziar Moradi-Lakeh Mehdi Moradinazar Paula Moraga Lidia Morawska Abbas Mosapour Seyyed Meysam Mousavi Ulrich Otto Mueller Atalay Goshu Muluneh Ghulam Mustafa Behnam Nabavizadeh Mehdi Naderi Ahamarshan Jayaraman Nagarajan Azin Nahvijou Farid Najafi Vinay Nangia Duduzile Edith Ndwandwe Nahid Neamati Ionut Negoi Ruxandra Irina Negoi Josephine W Ngunjiri Huong Lan Thi Nguyen Long Hoang Nguyen Son Hoang Nguyen Katie R Nielsen Dina Nur Anggraini Ningrum Yirga Legesse Nirayo Molly R Nixon Chukwudi A Nnaji Marzieh Nojomi Mehdi Noroozi Shirin Nosratnejad Jean Jacques Noubiap Soraya Nouraei Motlagh Richard Ofori-Asenso Felix Akpojene Ogbo Kelechi E Oladimeji Andrew T Olagunju Meysam Olfatifar Solomon Olum Bolajoko Olubukunola Olusanya Mojisola Morenike Oluwasanu Obinna E Onwujekwe Eyal Oren Doris D V Ortega-Altamirano Alberto Ortiz Osayomwanbo Osarenotor Frank B Osei Aaron E Osgood-Zimmerman Stanislav S Otstavnov Mayowa Ojo Owolabi Mahesh P A Abdol Sattar Pagheh Smita Pakhale Songhomitra Panda-Jonas Animika Pandey Eun-Kee Park Hadi Parsian Tahereh Pashaei Sangram Kishor Patel Veincent Christian Filipino Pepito Alexandre Pereira Samantha Perkins Brandon V Pickering Thomas Pilgrim Majid Pirestani Bakhtiar Piroozi Meghdad Pirsaheb Oleguer Plana-Ripoll Hadi Pourjafar Parul Puri Mostafa Qorbani Hedley Quintana Mohammad Rabiee Navid Rabiee Amir Radfar Alireza Rafiei Fakher Rahim Zohreh Rahimi Vafa Rahimi-Movaghar Shadi Rahimzadeh Fatemeh Rajati Sree Bhushan Raju Azra Ramezankhani Chhabi Lal Ranabhat Davide Rasella Vahid Rashedi Lal Rawal Robert C Reiner Andre M N Renzaho Satar Rezaei Aziz Rezapour Seyed Mohammad Riahi Ana Isabel Ribeiro Leonardo Roever Elias Merdassa Roro Max Roser Gholamreza Roshandel Daem Roshani Ali Rostami Enrico Rubagotti Salvatore Rubino Siamak Sabour Nafis Sadat Ehsan Sadeghi Reza Saeedi Yahya Safari Roya Safari-Faramani Mahdi Safdarian Amirhossein Sahebkar Mohammad Reza Salahshoor Nasir Salam Payman Salamati Farkhonde Salehi Saleh Salehi Zahabi Yahya Salimi Hamideh Salimzadeh Joshua A Salomon Evanson Zondani Sambala Abdallah M Samy Milena M Santric Milicevic Bruno Piassi Sao Jose Sivan Yegnanarayana Iyer Saraswathy Rodrigo Sarmiento-Suárez Benn Sartorius Brijesh Sathian Sonia Saxena Alyssa N Sbarra Lauren E Schaeffer David C Schwebel Sadaf G Sepanlou Seyedmojtaba Seyedmousavi Faramarz Shaahmadi Masood Ali Shaikh Mehran Shams-Beyranvand Amir Shamshirian Morteza Shamsizadeh Kiomars Sharafi Mehdi Sharif Mahdi Sharif-Alhoseini Hamid Sharifi Jayendra Sharma Rajesh Sharma Aziz Sheikh Chloe Shields Mika Shigematsu Rahman Shiri Ivy Shiue Kerem Shuval Tariq J Siddiqi João Pedro Silva Jasvinder A Singh Dhirendra Narain Sinha Malede Mequanent Sisay Solomon Sisay Karen Sliwa David L Smith Ranjani Somayaji Moslem Soofi Joan B Soriano Chandrashekhar T Sreeramareddy Agus Sudaryanto Mu'awiyyah Babale Sufiyan Bryan L Sykes P N Sylaja Rafael Tabarés-Seisdedos Karen M Tabb Takahiro Tabuchi Nuno Taveira Mohamad-Hani Temsah Abdullah Sulieman Terkawi Zemenu Tadesse Tessema Kavumpurathu Raman Thankappan Sathish Thirunavukkarasu Quyen G To Marcos Roberto Tovani-Palone Bach Xuan Tran Khanh Bao Tran Irfan Ullah Muhammad Shariq Usman Olalekan A Uthman Amir Vahedian-Azimi Pascual R Valdez Job F M van Boven Tommi Juhani Vasankari Yasser Vasseghian Yousef Veisani Narayanaswamy Venketasubramanian Francesco S Violante Sergey Konstantinovitch Vladimirov Vasily Vlassov Theo Vos Giang Thu Vu Isidora S Vujcic Yasir Waheed Jon Wakefield Haidong Wang Yafeng Wang Yuan-Pang Wang Joseph L Ward Robert G Weintraub Kidu Gidey Weldegwergs Girmay Teklay Weldesamuel Ronny Westerman Charles Shey Wiysonge Dawit Zewdu Wondafrash Lauren Woyczynski Ai-Min Wu Gelin Xu Abbas Yadegar Tomohide Yamada Vahid Yazdi-Feyzabadi Christopher Sabo Yilgwan Paul Yip Naohiro Yonemoto Javad Yoosefi Lebni Mustafa Z Younis Mahmoud Yousefifard Hebat-Allah Salah A Yousof Chuanhua Yu Hasan Yusefzadeh Erfan Zabeh Telma Zahirian Moghadam Sojib Bin Zaman Mohammad Zamani Hamed Zandian Alireza Zangeneh Taddese Alemu Zerfu Yunquan Zhang Arash Ziapour Sanjay Zodpey Christopher J L Murray Simon I Hay

Nature 2019 10 16;574(7778):353-358. Epub 2019 Oct 16.

Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2-to end preventable child deaths by 2030-we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000-2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations.
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http://dx.doi.org/10.1038/s41586-019-1545-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6800389PMC
October 2019

Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-Years for 29 Cancer Groups, 1990 to 2017: A Systematic Analysis for the Global Burden of Disease Study.

Authors:
Christina Fitzmaurice Degu Abate Naghmeh Abbasi Hedayat Abbastabar Foad Abd-Allah Omar Abdel-Rahman Ahmed Abdelalim Amir Abdoli Ibrahim Abdollahpour Abdishakur S M Abdulle Nebiyu Dereje Abebe Haftom Niguse Abraha Laith Jamal Abu-Raddad Ahmed Abualhasan Isaac Akinkunmi Adedeji Shailesh M Advani Mohsen Afarideh Mahdi Afshari Mohammad Aghaali Dominic Agius Sutapa Agrawal Ayat Ahmadi Elham Ahmadian Ehsan Ahmadpour Muktar Beshir Ahmed Mohammad Esmaeil Akbari Tomi Akinyemiju Ziyad Al-Aly Assim M AlAbdulKader Fares Alahdab Tahiya Alam Genet Melak Alamene Birhan Tamene T Alemnew Kefyalew Addis Alene Cyrus Alinia Vahid Alipour Syed Mohamed Aljunid Fatemeh Allah Bakeshei Majid Abdulrahman Hamad Almadi Amir Almasi-Hashiani Ubai Alsharif Shirina Alsowaidi Nelson Alvis-Guzman Erfan Amini Saeed Amini Yaw Ampem Amoako Zohreh Anbari Nahla Hamed Anber Catalina Liliana Andrei Mina Anjomshoa Fereshteh Ansari Ansariadi Ansariadi Seth Christopher Yaw Appiah Morteza Arab-Zozani Jalal Arabloo Zohreh Arefi Olatunde Aremu Habtamu Abera Areri Al Artaman Hamid Asayesh Ephrem Tsegay Asfaw Alebachew Fasil Ashagre Reza Assadi Bahar Ataeinia Hagos Tasew Atalay Zerihun Ataro Suleman Atique Marcel Ausloos Leticia Avila-Burgos Euripide F G A Avokpaho Ashish Awasthi Nefsu Awoke Beatriz Paulina Ayala Quintanilla Martin Amogre Ayanore Henok Tadesse Ayele Ebrahim Babaee Umar Bacha Alaa Badawi Mojtaba Bagherzadeh Eleni Bagli Senthilkumar Balakrishnan Abbas Balouchi Till Winfried Bärnighausen Robert J Battista Masoud Behzadifar Meysam Behzadifar Bayu Begashaw Bekele Yared Belete Belay Yaschilal Muche Belayneh Kathleen Kim Sachiko Berfield Adugnaw Berhane Eduardo Bernabe Mircea Beuran Nickhill Bhakta Krittika Bhattacharyya Belete Biadgo Ali Bijani Muhammad Shahdaat Bin Sayeed Charles Birungi Catherine Bisignano Helen Bitew Tone Bjørge Archie Bleyer Kassawmar Angaw Bogale Hunduma Amensisa Bojia Antonio M Borzì Cristina Bosetti Ibrahim R Bou-Orm Hermann Brenner Jerry D Brewer Andrey Nikolaevich Briko Nikolay Ivanovich Briko Maria Teresa Bustamante-Teixeira Zahid A Butt Giulia Carreras Juan J Carrero Félix Carvalho Clara Castro Franz Castro Ferrán Catalá-López Ester Cerin Yazan Chaiah Wagaye Fentahun Chanie Vijay Kumar Chattu Pankaj Chaturvedi Neelima Singh Chauhan Mohammad Chehrazi Peggy Pei-Chia Chiang Tesfaye Yitna Chichiabellu Onyema Greg Chido-Amajuoyi Odgerel Chimed-Ochir Jee-Young J Choi Devasahayam J Christopher Dinh-Toi Chu Maria-Magdalena Constantin Vera M Costa Emanuele Crocetti Christopher Stephen Crowe Maria Paula Curado Saad M A Dahlawi Giovanni Damiani Amira Hamed Darwish Ahmad Daryani José das Neves Feleke Mekonnen Demeke Asmamaw Bizuneh Demis Birhanu Wondimeneh Demissie Gebre Teklemariam Demoz Edgar Denova-Gutiérrez Afshin Derakhshani Kalkidan Solomon Deribe Rupak Desai Beruk Berhanu Desalegn Melaku Desta Subhojit Dey Samath Dhamminda Dharmaratne Meghnath Dhimal Daniel Diaz Mesfin Tadese Tadese Dinberu Shirin Djalalinia David Teye Doku Thomas M Drake Manisha Dubey Eleonora Dubljanin Eyasu Ejeta Duken Hedyeh Ebrahimi Andem Effiong Aziz Eftekhari Iman El Sayed Maysaa El Sayed Zaki Shaimaa I El-Jaafary Ziad El-Khatib Demelash Abewa Elemineh Hajer Elkout Richard G Ellenbogen Aisha Elsharkawy Mohammad Hassan Emamian Daniel Adane Endalew Aman Yesuf Endries Babak Eshrati Ibtihal Fadhil Vahid Fallah Omrani Mahbobeh Faramarzi Mahdieh Abbasalizad Farhangi Andrea Farioli Farshad Farzadfar Netsanet Fentahun Eduarda Fernandes Garumma Tolu Feyissa Irina Filip Florian Fischer James L Fisher Lisa M Force Masoud Foroutan Marisa Freitas Takeshi Fukumoto Neal D Futran Silvano Gallus Fortune Gbetoho Gankpe Reta Tsegaye Gayesa Tsegaye Tewelde Gebrehiwot Gebreamlak Gebremedhn Gebremeskel Getnet Azeze Gedefaw Belayneh K Gelaw Birhanu Geta Sefonias Getachew Kebede Embaye Gezae Mansour Ghafourifard Alireza Ghajar Ahmad Ghashghaee Asadollah Gholamian Paramjit Singh Gill Themba T G Ginindza Alem Girmay Muluken Gizaw Ricardo Santiago Gomez Sameer Vali Gopalani Giuseppe Gorini Bárbara Niegia Garcia Goulart Ayman Grada Maximiliano Ribeiro Guerra Andre Luiz Sena Guimaraes Prakash C Gupta Rahul Gupta Kishor Hadkhale Arvin Haj-Mirzaian Arya Haj-Mirzaian Randah R Hamadeh Samer Hamidi Lolemo Kelbiso Hanfore Josep Maria Haro Milad Hasankhani Amir Hasanzadeh Hamid Yimam Hassen Roderick J Hay Simon I Hay Andualem Henok Nathaniel J Henry Claudiu Herteliu Hagos D Hidru Chi Linh Hoang Michael K Hole Praveen Hoogar Nobuyuki Horita H Dean Hosgood Mostafa Hosseini Mehdi Hosseinzadeh Mihaela Hostiuc Sorin Hostiuc Mowafa Househ Mohammedaman Mama Hussen Bogdan Ileanu Milena D Ilic Kaire Innos Seyed Sina Naghibi Irvani Kufre Robert Iseh Sheikh Mohammed Shariful Islam Farhad Islami Nader Jafari Balalami Morteza Jafarinia Leila Jahangiry Mohammad Ali Jahani Nader Jahanmehr Mihajlo Jakovljevic Spencer L James Mehdi Javanbakht Sudha Jayaraman Sun Ha Jee Ensiyeh Jenabi Ravi Prakash Jha Jost B Jonas Jitendra Jonnagaddala Tamas Joo Suresh Banayya Jungari Mikk Jürisson Ali Kabir Farin Kamangar André Karch Narges Karimi Ansar Karimian Amir Kasaeian Gebremicheal Gebreslassie Kasahun Belete Kassa Tesfaye Dessale Kassa Mesfin Wudu Kassaw Anil Kaul Peter Njenga Keiyoro Abraham Getachew Kelbore Amene Abebe Kerbo Yousef Saleh Khader Maryam Khalilarjmandi Ejaz Ahmad Khan Gulfaraz Khan Young-Ho Khang Khaled Khatab Amir Khater Maryam Khayamzadeh Maryam Khazaee-Pool Salman Khazaei Abdullah T Khoja Mohammad Hossein Khosravi Jagdish Khubchandani Neda Kianipour Daniel Kim Yun Jin Kim Adnan Kisa Sezer Kisa Katarzyna Kissimova-Skarbek Hamidreza Komaki Ai Koyanagi Kristopher J Krohn Burcu Kucuk Bicer Nuworza Kugbey Vivek Kumar Desmond Kuupiel Carlo La Vecchia Deepesh P Lad Eyasu Alem Lake Ayenew Molla Lakew Dharmesh Kumar Lal Faris Hasan Lami Qing Lan Savita Lasrado Paolo Lauriola Jeffrey V Lazarus James Leigh Cheru Tesema Leshargie Yu Liao Miteku Andualem Limenih Stefan Listl Alan D Lopez Platon D Lopukhov Raimundas Lunevicius Mohammed Madadin Sameh Magdeldin Hassan Magdy Abd El Razek Azeem Majeed Afshin Maleki Reza Malekzadeh Ali Manafi Navid Manafi Wondimu Ayele Manamo Morteza Mansourian Mohammad Ali Mansournia Lorenzo Giovanni Mantovani Saman Maroufizadeh Santi Martini S Martini Tivani Phosa Mashamba-Thompson Benjamin Ballard Massenburg Motswadi Titus Maswabi Manu Raj Mathur Colm McAlinden Martin McKee Hailemariam Abiy Alemu Meheretu Ravi Mehrotra Varshil Mehta Toni Meier Yohannes A Melaku Gebrekiros Gebremichael Meles Hagazi Gebre Meles Addisu Melese Mulugeta Melku Peter T N Memiah Walter Mendoza Ritesh G Menezes Shahin Merat Tuomo J Meretoja Tomislav Mestrovic Bartosz Miazgowski Tomasz Miazgowski Kebadnew Mulatu M Mihretie Ted R Miller Edward J Mills Seyed Mostafa Mir Hamed Mirzaei Hamid Reza Mirzaei Rashmi Mishra Babak Moazen Dara K Mohammad Karzan Abdulmuhsin Mohammad Yousef Mohammad Aso Mohammad Darwesh Abolfazl Mohammadbeigi Hiwa Mohammadi Moslem Mohammadi Mahdi Mohammadian Abdollah Mohammadian-Hafshejani Milad Mohammadoo-Khorasani Reza Mohammadpourhodki Ammas Siraj Mohammed Jemal Abdu Mohammed Shafiu Mohammed Farnam Mohebi Ali H Mokdad Lorenzo Monasta Yoshan Moodley Mahmood Moosazadeh Maryam Moossavi Ghobad Moradi Mohammad Moradi-Joo Maziar Moradi-Lakeh Farhad Moradpour Lidia Morawska Joana Morgado-da-Costa Naho Morisaki Shane Douglas Morrison Abbas Mosapour Seyyed Meysam Mousavi Achenef Asmamaw Muche Oumer Sada S Muhammed Jonah Musa Ashraf F Nabhan Mehdi Naderi Ahamarshan Jayaraman Nagarajan Gabriele Nagel Azin Nahvijou Gurudatta Naik Farid Najafi Luigi Naldi Hae Sung Nam Naser Nasiri Javad Nazari Ionut Negoi Subas Neupane Polly A Newcomb Haruna Asura Nggada Josephine W Ngunjiri Cuong Tat Nguyen Leila Nikniaz Dina Nur Anggraini Ningrum Yirga Legesse Nirayo Molly R Nixon Chukwudi A Nnaji Marzieh Nojomi Shirin Nosratnejad Malihe Nourollahpour Shiadeh Mohammed Suleiman Obsa Richard Ofori-Asenso Felix Akpojene Ogbo In-Hwan Oh Andrew T Olagunju Tinuke O Olagunju Mojisola Morenike Oluwasanu Abidemi E Omonisi Obinna E Onwujekwe Anu Mary Oommen Eyal Oren Doris D V Ortega-Altamirano Erika Ota Stanislav S Otstavnov Mayowa Ojo Owolabi Mahesh P A Jagadish Rao Padubidri Smita Pakhale Amir H Pakpour Adrian Pana Eun-Kee Park Hadi Parsian Tahereh Pashaei Shanti Patel Snehal T Patil Alyssa Pennini David M Pereira Cristiano Piccinelli Julian David Pillay Majid Pirestani Farhad Pishgar Maarten J Postma Hadi Pourjafar Farshad Pourmalek Akram Pourshams Swayam Prakash Narayan Prasad Mostafa Qorbani Mohammad Rabiee Navid Rabiee Amir Radfar Alireza Rafiei Fakher Rahim Mahdi Rahimi Muhammad Aziz Rahman Fatemeh Rajati Saleem M Rana Samira Raoofi Goura Kishor Rath David Laith Rawaf Salman Rawaf Robert C Reiner Andre M N Renzaho Nima Rezaei Aziz Rezapour Ana Isabel Ribeiro Daniela Ribeiro Luca Ronfani Elias Merdassa Roro Gholamreza Roshandel Ali Rostami Ragy Safwat Saad Parisa Sabbagh Siamak Sabour Basema Saddik Saeid Safiri Amirhossein Sahebkar Mohammad Reza Salahshoor Farkhonde Salehi Hosni Salem Marwa Rashad Salem Hamideh Salimzadeh Joshua A Salomon Abdallah M Samy Juan Sanabria Milena M Santric Milicevic Benn Sartorius Arash Sarveazad Brijesh Sathian Maheswar Satpathy Miloje Savic Monika Sawhney Mehdi Sayyah Ione J C Schneider Ben Schöttker Mario Sekerija Sadaf G Sepanlou Masood Sepehrimanesh Seyedmojtaba Seyedmousavi Faramarz Shaahmadi Hosein Shabaninejad Mohammad Shahbaz Masood Ali Shaikh Amir Shamshirian Morteza Shamsizadeh Heidar Sharafi Zeinab Sharafi Mehdi Sharif Ali Sharifi Hamid Sharifi Rajesh Sharma Aziz Sheikh Reza Shirkoohi Sharvari Rahul Shukla Si Si Soraya Siabani Diego Augusto Santos Silva Dayane Gabriele Alves Silveira Ambrish Singh Jasvinder A Singh Solomon Sisay Freddy Sitas Eugène Sobngwi Moslem Soofi Joan B Soriano Vasiliki Stathopoulou Mu'awiyyah Babale Sufiyan Rafael Tabarés-Seisdedos Takahiro Tabuchi Ken Takahashi Omid Reza Tamtaji Mohammed Rasoul Tarawneh Segen Gebremeskel Tassew Parvaneh Taymoori Arash Tehrani-Banihashemi Mohamad-Hani Temsah Omar Temsah Berhe Etsay Tesfay Fisaha Haile Tesfay Manaye Yihune Teshale Gizachew Assefa Tessema Subash Thapa Kenean Getaneh Tlaye Roman Topor-Madry Marcos Roberto Tovani-Palone Eugenio Traini Bach Xuan Tran Khanh Bao Tran Afewerki Gebremeskel Tsadik Irfan Ullah Olalekan A Uthman Marco Vacante Maryam Vaezi Patricia Varona Pérez Yousef Veisani Simone Vidale Francesco S Violante Vasily Vlassov Stein Emil Vollset Theo Vos Kia Vosoughi Giang Thu Vu Isidora S Vujcic Henry Wabinga Tesfahun Mulatu Wachamo Fasil Shiferaw Wagnew Yasir Waheed Fitsum Weldegebreal Girmay Teklay Weldesamuel Tissa Wijeratne Dawit Zewdu Wondafrash Tewodros Eshete Wonde Adam Belay Wondmieneh Hailemariam Mekonnen Workie Rajaram Yadav Abbas Yadegar Ali Yadollahpour Mehdi Yaseri Vahid Yazdi-Feyzabadi Alex Yeshaneh Mohammed Ahmed Yimam Ebrahim M Yimer Engida Yisma Naohiro Yonemoto Mustafa Z Younis Bahman Yousefi Mahmoud Yousefifard Chuanhua Yu Erfan Zabeh Vesna Zadnik Telma Zahirian Moghadam Zoubida Zaidi Mohammad Zamani Hamed Zandian Alireza Zangeneh Leila Zaki Kazem Zendehdel Zerihun Menlkalew Zenebe Taye Abuhay Zewale Arash Ziapour Sanjay Zodpey Christopher J L Murray

JAMA Oncol 2019 12;5(12):1749-1768

Institute for Health Metrics and Evaluation, University of Washington, Seattle.

Importance: Cancer and other noncommunicable diseases (NCDs) are now widely recognized as a threat to global development. The latest United Nations high-level meeting on NCDs reaffirmed this observation and also highlighted the slow progress in meeting the 2011 Political Declaration on the Prevention and Control of Noncommunicable Diseases and the third Sustainable Development Goal. Lack of situational analyses, priority setting, and budgeting have been identified as major obstacles in achieving these goals. All of these have in common that they require information on the local cancer epidemiology. The Global Burden of Disease (GBD) study is uniquely poised to provide these crucial data.

Objective: To describe cancer burden for 29 cancer groups in 195 countries from 1990 through 2017 to provide data needed for cancer control planning.

Evidence Review: We used the GBD study estimation methods to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life-years (DALYs). Results are presented at the national level as well as by Socio-demographic Index (SDI), a composite indicator of income, educational attainment, and total fertility rate. We also analyzed the influence of the epidemiological vs the demographic transition on cancer incidence.

Findings: In 2017, there were 24.5 million incident cancer cases worldwide (16.8 million without nonmelanoma skin cancer [NMSC]) and 9.6 million cancer deaths. The majority of cancer DALYs came from years of life lost (97%), and only 3% came from years lived with disability. The odds of developing cancer were the lowest in the low SDI quintile (1 in 7) and the highest in the high SDI quintile (1 in 2) for both sexes. In 2017, the most common incident cancers in men were NMSC (4.3 million incident cases); tracheal, bronchus, and lung (TBL) cancer (1.5 million incident cases); and prostate cancer (1.3 million incident cases). The most common causes of cancer deaths and DALYs for men were TBL cancer (1.3 million deaths and 28.4 million DALYs), liver cancer (572 000 deaths and 15.2 million DALYs), and stomach cancer (542 000 deaths and 12.2 million DALYs). For women in 2017, the most common incident cancers were NMSC (3.3 million incident cases), breast cancer (1.9 million incident cases), and colorectal cancer (819 000 incident cases). The leading causes of cancer deaths and DALYs for women were breast cancer (601 000 deaths and 17.4 million DALYs), TBL cancer (596 000 deaths and 12.6 million DALYs), and colorectal cancer (414 000 deaths and 8.3 million DALYs).

Conclusions And Relevance: The national epidemiological profiles of cancer burden in the GBD study show large heterogeneities, which are a reflection of different exposures to risk factors, economic settings, lifestyles, and access to care and screening. The GBD study can be used by policy makers and other stakeholders to develop and improve national and local cancer control in order to achieve the global targets and improve equity in cancer care.
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http://dx.doi.org/10.1001/jamaoncol.2019.2996DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6777271PMC
December 2019

Spatial clustering of notified tuberculosis in Ethiopia: A nationwide study.

PLoS One 2019 9;14(8):e0221027. Epub 2019 Aug 9.

Faculty of Health Sciences, Curtin University, Perth, Western Australia, Australia.

Background: Tuberculosis (TB) remains a major health problem worldwide and in Ethiopia. This study aimed to investigate the spatial distributions of notified TB over the whole territory of Ethiopia and to quantify the role of health care access, environmental, socio-demographic, and behavioural factors associated with the clustering of TB.

Methods: A spatial analysis was conducted using national TB data reported between June 2016 and June 2017 in Ethiopia. Spatial clustering of TB was explored using Moran's I statistic and the local indicator of spatial autocorrelation (LISA). A multivariate Poisson regression model was developed with a conditional autoregressive (CAR) prior structure and with posterior parameters estimated using Bayesian Markov chain Monte Carlo (MCMC) simulation with Gibbs sampling to investigate the drivers of the clustering.

Result: A total of 120,149 TB cases were reported from 745 districts in Ethiopia during the study period; 41,343 (34%) were bacteriologically confirmed new pulmonary TB and 33,997 (28%) were clinically diagnosed, new, smear-negative pulmonary TB patients. The nationwide annual incidence rate of notified TB was 112 per 100,000 population. The highest incidence was observed in three city administrative regions, namely Dire Dewa (348 cases per 100,000 population), Addis Ababa (262 per 100,000 population) and Harari (206 per 100,000 population), and the lowest incidence was observed in Somali region (51 per 100,000 population). High-high spatial clustering of notified TB was detected at Humera, Gog, and Surima district, and low-low clustering was detected in some districts located in the Somali region. Poor health care access (IRR = 0.78; 95%CI: 0.66, 0.90) and good knowledge about TB (IRR = 0.84; 95%CI: 0.73, 0.96) were negatively associated with the incidence of notified TB.

Conclusion: Substantial spatial clustering of notified TB was detected at region, zone and district level in Ethiopia. Health care access and knowledge about TB was associated with incidence of TB. This study may provide policy makers target hotspot areas, where national control programs could be implemented more efficiently for the prevention and control of TB, and to address potential under-reporting in poor access areas.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0221027PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6688824PMC
March 2020

Mapping tuberculosis treatment outcomes in Ethiopia.

BMC Infect Dis 2019 May 28;19(1):474. Epub 2019 May 28.

Faculty of Health Sciences, Curtin University, Perth, Western Australia, Australia.

Background: Tuberculosis (TB) is the leading cause of death from an infectious disease in Ethiopia, killing more than 30 thousand people every year. This study aimed to determine whether the rates of poor TB treatment outcome varied geographically across Ethiopia at district and zone levels and whether such variability was associated with socioeconomic, behavioural, health care access, or climatic conditions.

Methods: A geospatial analysis was conducted using national TB data reported to the health management information system (HMIS), for the period 2015-2017. The prevalence of poor TB treatment outcomes was calculated by dividing the sum of treatment failure, death and loss to follow-up by the total number of TB patients. Binomial logistic regression models were computed and a spatial analysis was performed using a Bayesian framework. Estimates of parameters were generated using Markov chain Monte Carlo (MCMC) simulation. Geographic clustering was assessed using the Getis-Ord Gi* statistic, and global and local Moran's I statistics.

Results: A total of 223,244 TB patients were reported from 722 districts in Ethiopia during the study period. Of these, 63,556 (28.5%) were cured, 139,633 (62.4%) completed treatment, 6716 (3.0%) died, 1459 (0.7%) had treatment failure, and 12,200 (5.5%) were lost to follow-up. The overall prevalence of a poor TB treatment outcome was 9.0% (range, 1-58%). Hot-spots and clustering of poor TB treatment outcomes were detected in districts near the international borders in Afar, Gambelia, and Somali regions and cold spots were detected in Oromia and Amhara regions. Spatial clustering of poor TB treatment outcomes was positively associated with the proportion of the population with low wealth index (OR: 1.01; 95%CI: 1.0, 1.01), the proportion of the population with poor knowledge about TB (OR: 1.02; 95%CI: 1.01, 1.03), and higher annual mean temperature per degree Celsius (OR: 1.15; 95% CI: 1.08, 1.21).

Conclusions: This study showed significant spatial variation in poor TB treatment outcomes in Ethiopia that was related to underlying socioeconomic status, knowledge about TB, and climatic conditions. Clinical and public health interventions should be targeted in hot spot areas to reduce poor TB treatment outcomes and to achieve the national End-TB Strategy targets.
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http://dx.doi.org/10.1186/s12879-019-4099-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6540408PMC
May 2019

Risk factors for multidrug-resistant tuberculosis in northwest Ethiopia: A case-control study.

Transbound Emerg Dis 2019 Jul 15;66(4):1611-1618. Epub 2019 Apr 15.

School of Public Health, Curtin University, Bentley, WA, Australia.

Ethiopia is one of 30-high burden multidrug-resistant tuberculosis (MDR-TB) countries globally. The aim of this study was to describe the characteristics of patients with MDR-TB and to investigate risk factors for MDR-TB relative to having drug-susceptible tuberculosis (TB), in northwest Ethiopia. A hospital-based, unmatched case-control study was conducted. Cases were all MDR-TB patients (i.e., resistant to at least rifampicin and isoniazid) who were confirmed by culture and drug-susceptibility testing whilst enrolled on treatment at Gondar University Hospital. Controls were all drug-susceptible tuberculosis (DS-TB) patients who were confirmed by Gene Xpert MTB/RIF at Gondar University Hospital. Univariable and multivariable logistic regression models were used for comparisons, and odds ratios with 95% confidence intervals (CI) were computed to measure the strength of association between the dependent and independent variables. A total of 452 patients (242 MDR-TB and 210 DS-TB) were included in this study. The mean age of the study participants was 33 years (SD ± 14 years). Approximately one-fifth (78, 17%) of all study participants were human immunodeficiency virus (HIV) positive; 21% (51) of cases and 13% (27) of controls. Risk factors associated with MDR-TB were a history of previous TB treatment (Adjusted Odds Ratio (AOR): 83.8; 95% CI: 40.7, 172.5), low educational status (AOR: 5.32; 95% CI: 1.43, 19.81); and ages less than 20 years (AOR: 9.01; 95% CI: 2.30, 35.25) and 21-30 years (AOR: 2.61; 95% CI: 1.02, 6.64). HIV infection was also significantly associated with MDR-TB among new TB patients (AOR: 5.55; 95% CI: 1.17, 26.20). This study shows that clinical and demographic features can be used to indicate higher risks of drug resistance in this setting.
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http://dx.doi.org/10.1111/tbed.13188DOI Listing
July 2019

Knowledge and practice of health workers about control and prevention of multidrug-resistant tuberculosis in referral hospitals, Ethiopia: a cross-sectional study.

BMJ Open 2019 02 19;9(2):e022948. Epub 2019 Feb 19.

Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.

Objective: The aim of this study was to assess the knowledge and practice of health workers about multidrug-resistant tuberculosis (MDR-TB) prevention and control.

Study Design And Settings: A cross-sectional study was conducted at Gondar University Referral Hospital and Felege Hiwot Referral Hospital.

Participants: Randomly selected health workers (ie, medical doctor, nurse, health officer, pharmacy, medical laboratory and midwifery) were the study participants.

Outcome Measures: The main outcomes were knowledge and self-reported practice of health workers about MDR-TB.

Results: A total of 377 health workers (with a response rate of 93.7%) participated in the study. The majority of respondents were nurses (52.5%, n=198) and medical doctors (15.6%, n=59). The mean knowledge score was seven out of 10; 149 (39.5%) of respondents scored seven or more which was considered as good knowledge. MDR-TB knowledge of health workers was significantly associated with having a postgraduate degree (adjusted odds ratio (AOR)=5.78; 95% CI 2.33 to 14.33), taking infection prevention training (AOR=1.79; 95% CI 1.00, to 3.17) and having a history of tuberculosis (TB) (AOR=1.85; 95% CI 1.12, to 3.03). The mean self-reported practice score was four out of seven; one-fifth (19.6%) of respondents scored four or more which was considered as good practice. Self-reported practice of health workers was significantly associated with working at internal medicine (AOR=4.64; 95% CI 1.99, to 10.81) and paediatrics (AOR=3.85; 95% CI 1.11, to 13.34) wards, being in the age groups of 26-30 years (AOR=2.70; 95% CI 1.27, to 5.76), and 30 years and above (AOR=4.42; 95% CI 1.77, to 11.00).

Conclusions: This study found low knowledge and self-reported practice score among health workers. MDR-TB knowledge of health workers was significantly associated with educational status, infection prevention training and previous history of TB. This finding highlights the potential of providing MDR-TB training for health workers to increase their knowledge about MDR-TB.
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http://dx.doi.org/10.1136/bmjopen-2018-022948DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6368005PMC
February 2019

Methods used in the spatial analysis of tuberculosis epidemiology: a systematic review.

BMC Med 2018 10 18;16(1):193. Epub 2018 Oct 18.

Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia.

Background: Tuberculosis (TB) transmission often occurs within a household or community, leading to heterogeneous spatial patterns. However, apparent spatial clustering of TB could reflect ongoing transmission or co-location of risk factors and can vary considerably depending on the type of data available, the analysis methods employed and the dynamics of the underlying population. Thus, we aimed to review methodological approaches used in the spatial analysis of TB burden.

Methods: We conducted a systematic literature search of spatial studies of TB published in English using Medline, Embase, PsycInfo, Scopus and Web of Science databases with no date restriction from inception to 15 February 2017. The protocol for this systematic review was prospectively registered with PROSPERO ( CRD42016036655 ).

Results: We identified 168 eligible studies with spatial methods used to describe the spatial distribution (n = 154), spatial clusters (n = 73), predictors of spatial patterns (n = 64), the role of congregate settings (n = 3) and the household (n = 2) on TB transmission. Molecular techniques combined with geospatial methods were used by 25 studies to compare the role of transmission to reactivation as a driver of TB spatial distribution, finding that geospatial hotspots are not necessarily areas of recent transmission. Almost all studies used notification data for spatial analysis (161 of 168), although none accounted for undetected cases. The most common data visualisation technique was notification rate mapping, and the use of smoothing techniques was uncommon. Spatial clusters were identified using a range of methods, with the most commonly employed being Kulldorff's spatial scan statistic followed by local Moran's I and Getis and Ord's local Gi(d) tests. In the 11 papers that compared two such methods using a single dataset, the clustering patterns identified were often inconsistent. Classical regression models that did not account for spatial dependence were commonly used to predict spatial TB risk. In all included studies, TB showed a heterogeneous spatial pattern at each geographic resolution level examined.

Conclusions: A range of spatial analysis methodologies has been employed in divergent contexts, with all studies demonstrating significant heterogeneity in spatial TB distribution. Future studies are needed to define the optimal method for each context and should account for unreported cases when using notification data where possible. Future studies combining genotypic and geospatial techniques with epidemiologically linked cases have the potential to provide further insights and improve TB control.
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http://dx.doi.org/10.1186/s12916-018-1178-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6193308PMC
October 2018

Anemia severity among children aged 6-59 months in Gondar town, Ethiopia: a community-based cross-sectional study.

Ital J Pediatr 2018 Sep 3;44(1):107. Epub 2018 Sep 3.

School of Medicine, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.

Background: Anemia is a public health problem affecting both developed and developing countries. Childhood anemia is associated with serious consequences including growth retardation, impaired motor and cognitive development, and increased morbidity and mortality. Hence, this study aimed at assessing the prevalence and factors associated with severity of anemia among children aged 6-59 months in Gondar town, northwest Ethiopia.

Method: A community-based cross-sectional study was conducted. A multi-stage sampling technique was employed to select study participants. Socio demographic and socioeconomic data were collected using a pre-tested structured questionnaire. Anthropometric measurements were taken as per WHO recommendation. Hemoglobin (Hb) concentration was measured using a portable HemoCue301 instrument (A Quest Diagnostic Company, Sweden). Mild anemia corresponds to a level of adjusted Hb of 10.0-10.9 g/dl; moderate anemia corresponds to a level of 7.0-9.9 g/dl, while severe anemia corresponds to a level less than 7.0 g/dl. Descriptive statistics were used to describe the study participants. Both bivariable and multivariable ordinal logistic regression were done, and proportional odds ratio (POR) with a 95% confidence interval (CI) was reported to show the strength of association. A p-value < 0.05 was considered statistically significant.

Result: Out of the total of 707 children included in this study, more than half (53.5%) of them were male. The median age of children was 30 months. Two hundred two (28.6%) of children were anemic: 124(17.5%) were mildly anemic, 73(10.3%) were moderately anemic, and 5 (0.7%) were severely anemic. The young age of the child, low frequency of child complementary feeding per day, primary maternal educational status, unmarried maternal marital status, and home delivery were factors associated with severity of childhood anemia.

Conclusion: Anemia among children aged 6-59 months in Gondar Town was a moderate public health problem. Improving access to education, providing regular health education about childcare and child feeding practices, strengthening the socioeconomic support for single-parent families and conducting regular community-based screening are recommended to reduce childhood anemia.
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http://dx.doi.org/10.1186/s13052-018-0547-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6122612PMC
September 2018

Mental health disorders, social stressors, and health-related quality of life in patients with multidrug-resistant tuberculosis: A systematic review and meta-analysis.

J Infect 2018 11 20;77(5):357-367. Epub 2018 Jul 20.

Research School of Population Health, College of Health and Medicine, The Australian National University, Canberra, Australia; Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden.

Background: Mental health disorders, social stress, and poor health-related quality of life are commonly reported among people with tuberculosis (TB). We conducted a systematic review and meta-analysis to quantify mental health disorders, social stressors, and health-related quality of life in patients with multidrug-resistant tuberculosis (MDR-TB).

Methods: We searched PubMed, SCOPUS, ProQuest, Web of Science, and PsycINFO databases for studies that reported data on mental health disorders, social stressors, and health-related quality of life among MDR-TB patients. Hand-searching the reference lists of included studies was also performed. Studies were selected according to pre-defined selection criteria and data were extracted by two authors. Pooled prevalence and weighted mean difference estimates were performed using random-effects meta-analysis. Heterogeneity was explored using meta-regression, and subgroup analyses were performed.

Results: We included a total of 40 studies that were conducted in 20 countries. Depression, anxiety, and psychosis were the most common mental health disorders reported in the studies. The overall pooled prevalence was 25% (95% confidence interval (CI): 14, 39) for depression, 24% (95% CI: 2, 57) for anxiety, and 10% (95% CI: 7, 14) for psychosis. There was substantial heterogeneity in the estimates. The stratified analysis showed that the prevalence of psychosis was 4% (95% CI: 0, 22) before MDR-TB treatment commencement, and 9% (95% CI: 5, 13) after MDR-TB treatment commencement. The most common social stressors reported were stigma, discrimination, isolation, and a lack of social support. Health-related quality of life was significantly lower among MDR-TB patients when compared to drug-susceptible TB patients (Q = 9.88, p = 0.01, I = 80%).

Conclusions: This review found that mental health and social functioning are compromised in a significant proportion of MDR-TB patients, a finding confirmed by the poor health-related quality of life reported. Thus, there is a substantial need for integrating mental health services, social protection and social support into the clinical and programmatic management of MDR-TB.
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http://dx.doi.org/10.1016/j.jinf.2018.07.007DOI Listing
November 2018

Contraceptive use and method preference among HIV-positive women in Amhara region, Ethiopia.

BMC Womens Health 2018 06 18;18(1):97. Epub 2018 Jun 18.

School of Nursing, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.

Background: Providing preferred methods of contraceptive for HIV-positive women and avoiding unintended pregnancy is one of the primary means of preventing mother to child transmission of HIV. This study assessed the prevalence of contraceptive use and method preference among HIV-positive women in Amhara region, Ethiopia.

Methods: A cross-sectional survey was conducted among HIV-positive women in three referral hospitals of Amhara region. Data were collected by interviewing HIV-positive women using a pre-tested and structured questionnaire. A binary logistic regression model was used to identify factors associated with contraceptive use, and odd ratio with 95% confidence interval (CI) was calculated to measure the strength of association.

Results: A total of 803 women living with HIV (with a response rate of 95.4%) were interviewed. The mean age of the study participants was 32.2 years (SD ± 6.2 years). The prevalence of current contraceptive use was 30.3% (95% CI: 27.0-33.7%). The preferred and most commonly used contraceptive methods were injectable (42.8%) and male condom (32.9%). Younger age group (15-24 years) (AOR = 9.67; 95%CI: 3.45, 27.10), one or more number of living children (AOR = 4.01; 95%CI: 2.07, 7.79), HIV diagnosis > 2-4 years (AOR = 2.37; 95%CI: 1.10, 5.08), and having high CD4 count > 500 cell/ul (AOR = 3.25; 95% CI: 1.42, 7.44) were significantly associated with contraceptive use.

Conclusion: The prevalence of contraceptive use among HIV-positive women in Amhara region referral hospitals is low, which suggests a high risk of unintended pregnancy. Injectable and male condoms are the most preferred type of contraceptive methods. Thus, it is better to integrate these contraceptive methods with ART clinic.
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http://dx.doi.org/10.1186/s12905-018-0608-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6006570PMC
June 2018

Comparison of the validity of smear and culture conversion as a prognostic marker of treatment outcome in patients with multidrug-resistant tuberculosis.

PLoS One 2018 23;13(5):e0197880. Epub 2018 May 23.

Research School of Population Health, College of Health and Medicine, The Australian National University, Canberra, Australian Capital Territory, Australia.

Background: The World Health Organization (WHO) has conditionally recommended the use of sputum smear microscopy and culture examination for the monitoring of multidrug-resistant tuberculosis (MDR-TB) treatment. We aimed to assess and compare the validity of smear and culture conversion at different time points during treatment for MDR-TB, as a prognostic marker for end-of-treatment outcomes.

Methods: We undertook a retrospective observational cohort study using data obtained from Hunan Chest Hospital, China and Gondar University Hospital, Ethiopia. The sensitivity and specificity of culture and sputum smear conversion for predicting treatment outcomes were analysed using a random-effects generalized linear mixed model.

Results: A total of 429 bacteriologically confirmed MDR-TB patients with a culture and smear positive result were included. Overall, 345 (80%) patients had a successful treatment outcome, and 84 (20%) patients had poor treatment outcomes. The sensitivity of smear and culture conversion to predict a successful treatment outcome were: 77.9% and 68.9% at 2 months after starting treatment (difference between tests, p = 0.007); 95.9% and 92.7% at 4 months (p = 0.06); 97.4% and 96.2% at 6 months (p = 0.386); and 99.4% and 98.9% at 12 months (p = 0.412), respectively. The specificity of smear and culture non-conversion to predict a poor treatment outcome were: 41.6% and 60.7% at 2 months (p = 0.012); 23.8% and 48.8% at 4 months (p<0.001); and 20.2% and 42.8% at 6 months (p<0.001); and 15.4% and 32.1% (p<0.001) at 12 months, respectively. The sensitivity of culture and smear conversion increased as the month of conversion increased but at the cost of decreased specificity. The optimum time points after conversion to provide the best prognostic marker of a successful treatment outcome were between two and four months after treatment commencement for smear, and between four and six months for culture. The common optimum time point for smear and culture conversion was four months. At this time point, culture conversion (AUROC curve = 0.71) was significantly better than smear conversion (AUROC curve = 0.6) in predicting successful treatment outcomes (p < 0.001). However, the validity of smear conversion (AUROC curve = 0.7) was equivalent to culture conversion (AUROC curve = 0.71) in predicting treatment outcomes when demographic and clinical factors were included in the model. The positive and negative predictive values for smear conversion were: 57.3% and 65.7% at two months, 55.7% and 85.4% at four months, and 55.0% and 88.6% at six months; and for culture conversions it was: 63.7% and 66.2% at two months, 64.4% and 87.1% at four months, and 62.7% and 91.9% at six months, respectively.

Conclusions: The validity of smear conversion is significantly lower than culture conversion in predicting MDR-TB treatment outcomes. We support the WHO recommendation of using both smear and culture examination rather than smear alone for the monitoring of MDR-TB patients for a better prediction of successful treatment outcomes. The optimum time points to predict a future successful treatment outcome were between two and four months after treatment commencement for sputum smear conversion and between four and six months for culture conversion. The common optimum times for culture and smear conversion together was four months.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0197880PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5965863PMC
November 2018

Sequelae of multidrug-resistant tuberculosis: protocol for a systematic review and meta-analysis.

BMJ Open 2018 02 10;8(2):e019593. Epub 2018 Feb 10.

Research School of Population Health, College of Health and Medicine, Australian National University, Canberra, Australia.

Introduction: The sequelae of multidrug-resistant tuberculosis (MDR-TB) are poorly understood and inconsistently reported. We will aim to assess the existing evidence for the clinical, psychological, social and economic sequelae of MDR-TB and to assess the health-related quality of life in patients with MDR-TB.

Methods And Analysis: We will perform a systematic review and meta-analysis of published studies reporting sequelae of MDR-TB. We will search PubMed, SCOPUS, ProQuest, Web of Science and PsychINFO databases up to 5 September 2017. MDR-TB sequelae will include any clinical, psychological, social and economic effects as well as health-related quality of life that occur after MDR-TB treatment or illness. Two researchers will screen the titles and abstracts of all citations identified in our search, extract data, and assess the scientific quality using standardised formats. Providing there is appropriate comparability in the studies, we will use a random-effects meta-analysis model to produce pooled estimates of MDR-TB sequelae from the included studies. We will stratify the analyses based on treatment regimen, comorbidities (such as HIV status and diabetes mellitus), previous TB treatment history and study setting.

Ethics And Dissemination: As this study will be based on published data, ethical approval is not required. The final report will be disseminated through publication in a peer-reviewed scientific journal and will also be presented at relevant conferences.

Prospero Registration Number: CRD42017073182.
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http://dx.doi.org/10.1136/bmjopen-2017-019593DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829942PMC
February 2018

Spatiotemporal transmission and socio-climatic factors related to paediatric tuberculosis in north-western Ethiopia.

Geospat Health 2017 11 27;12(2):575. Epub 2017 Nov 27.

Research School of Population Health, College of Health and Medicine, The Australian National University, Canberra, Australia; Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar.

The burden of tuberculosis (TB) in children reflects continuing and recent transmission within a population. This study aimed to identify spatiotemporal and socio-climatic factors associated with paediatric TB in north-western Ethiopia. Multivariate Poisson regression models were computed using a Bayesian framework. Estimates of parameters were generated using Markov chain Monte Carlo simulation. A total of 2,240 children aged under 15 years diagnosed with TB during the years 2013- 2016 were included in the analysis. The annual TB incidence rates were 44 and 28 per 100,000 children, for children aged under 15 and 5 years, respectively. Spatial clustering of TB was observed in the border area of north-western Ethiopia. The spatio-temporal transmission of childhood TB was found to be associated with district level socio-climatic factors such as urbanisation [relative risk (RR): 1.8; 95% credible interval (CrI): 1.2, 2.6], lower educational status (RR: 1.5; 95% CrI: 1.0, 2.1), a high percentage of internal migration (RR: 1.3; 95% CrI: 1.0, 1.6), high temperature (RR: 1.3; 95% CrI: 1.0, 1.7) and high rainfall (RR: 1.5; 95% CrI: 1.1, 2.0). We conclude that interventions targeting hotspot districts with a high proportion of childhood TB are important to reduce TB transmission in northwest Ethiopia.
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http://dx.doi.org/10.4081/gh.2017.575DOI Listing
November 2017

Treatment outcomes of patients with multidrug-resistant and extensively drug resistant tuberculosis in Hunan Province, China.

BMC Infect Dis 2017 08 16;17(1):573. Epub 2017 Aug 16.

Department of Tuberculosis Control, Tuberculosis Control Institute of Hunan Province, Changsha city, Hunan Province, China.

Background: The worldwide emergence of multidrug-resistant tuberculosis (MDR-TB) and extensively drug-resistant tuberculosis (XDR-TB) has posed additional challenges for global tuberculosis (TB) control efforts, as limited treatment options are available and treatment outcomes are often sub-optimal. This study determined treatment outcomes among a cohort of MDR-TB and XDR-TB patients in Hunan Province, China, and identified factors associated with poor treatment outcomes.

Methods: We conducted a retrospective study using data obtained from medical records of TB patients in Hunan Chest Hospital, and from the internet-based TB management information system managed by the Tuberculosis Control Institute of Hunan Province, for the period 2011 to 2014. Treatment outcomes were assessed for patients diagnosed with MDR-TB (TB resistant to at least isoniazid and rifampicin) and XDR-TB (MDR-TB plus resistance to any fluoroquinolone and at least 1 second-line injectable drug). Cumulative incidence functions were used to estimate time to events (i.e. poor treatment outcomes, loss to follow-up, and unfavourable treatment outcomes); and a competing-risks survival regression model was used to identify predictors of treatment outcomes.

Result: Of 481 bacteriologically-confirmed patients, with a mean age of 40 years (standard deviation SD ± 13 years), 10 (2%) had XDR-TB and the remainder (471; 98%) had MDR-TB. For the entire cohort, treatment success was 57% (n = 275); 58% (n = 272) for MDR-TB and 30% (n = 3) for XDR-TB. Overall, 27% were lost to follow-up (n = 130), 27% (n = 126) for MDR-TB and 40% (n = 4) for XDR-TB; and 16% had a poor treatment outcome (n = 76), 15% for MDR-TB and 30% (n = 3) for XDR-TB. Of the 10 XDR-TB patients, 3 (30%) completed treatment, 3 (30%) died and 4 (40%) were lost to follow-up. Of the 471 MDR-TB patients, 258 (57%) were cured, 16 (3%) completed treatment, 13 (3%) died, 60 (13%) experienced treatment failure, and 126 (27%) were lost to follow-up. Resistance to ofloxacin was an independent predictor of poor (AHR = 3.1; 95%CI = 1.5, 6.3), and unfavourable (AHR = 1.7; 95%CI = 1.07, 2.9) treatment outcomes. Patients who started treatment during 2011-2012 (AHR = 2.8; 95% CI = 1.5, 5.3) and 2013 (AHR = 2.1; 95% CI = 1.2, 3.9) had poorer treatment outcomes compared to patients who started treatment during 2014.

Conclusion: Patients with MDR-TB and XDR-TB had low rates of treatment success in Hunan Province, especially among patients who started treatment during 2011 to 2013, with evidence of improved treatment outcomes in 2014. Resistance to ofloxacin was an independent predictor of poor treatment outcomes.
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http://dx.doi.org/10.1186/s12879-017-2662-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5559784PMC
August 2017

Transfusion-transmissible viral infections among blood donors at the North Gondar district blood bank, northwest Ethiopia: A three year retrospective study.

PLoS One 2017 5;12(7):e0180416. Epub 2017 Jul 5.

Department of Hematology and Immunohematology, School of Biomedical and Laboratory Sciences, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.

Background: Transfusion-transmissible viral infections, such as hepatitis C virus (HCV), hepatitis B virus (HBV), and human immunodeficiency virus (HIV), remain a major public health problem in developing countries. The prevalence of these viral infections among blood donors may reflect the burden of these diseases among populations. Therefore, the aim of this study was to assess the sero-prevalence of transfusion-transmissible viral infections among blood donors.

Methods: A retrospective study was conducted using data obtained from registration books of blood donors from the Ethiopian North Gondar District Blood Bank from 2010 to 2012. Descriptive statistics, such as percentages, medians and interquartile ranges were computed. A binary logistic regression model was fitted to identify factors associated with each viral infection. The odds ratio with a 99% confidence interval was calculated. A p-value < 0.01 was considered statistically significant.

Result: A total of 6,471 blood donors were included in the study. Of these, 5,311 (82.1%) were male, and 382 (5.9%) were voluntary blood donors. Overall, 424 (6.55%) of the blood donors were sero-reactive for at least one transfusion-transmissible viral infection. Of all study participants, 233 (3.6%) were sero-reactive for HBV, 145 (2.24%) were sero-reactive for HIV, and 51 (0.8%) were sero-reactive for HCV. Four (0.062%) of the study's participants were co-infected: 3 (75%) with HBV-HCV and 1 (25%) with HIV-HBV-HCV. Being a farmer, unemployed or employed donor was significantly associated with transfusion-transmissible viral infections compared to being a student donor.

Conclusion: The prevalence of transfusion-transmissible viral infections is substantial and has increased overtime. Hence, it demands more vigilance in routine screening of donated blood prior to transfusion. Further community-based studies to identify societal risk factors are necessary.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0180416PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5498040PMC
October 2017

Spatial patterns of multidrug resistant tuberculosis and relationships to socio-economic, demographic and household factors in northwest Ethiopia.

PLoS One 2017 9;12(2):e0171800. Epub 2017 Feb 9.

Research School of Population Health, College of Medicine, Biology and Environment, The Australian National University, Canberra, Australian Capital Territory, Australia.

Background: Understanding the geographical distribution of multidrug-resistant tuberculosis (MDR-TB) in high TB burden countries such as Ethiopia is crucial for effective control of TB epidemics in these countries, and thus globally. We present the first spatial analysis of multidrug resistant tuberculosis, and its relationship to socio-economic, demographic and household factors in northwest Ethiopia.

Methods: An ecological study was conducted using data on patients diagnosed with MDR-TB at the University of Gondar Hospital MDR-TB treatment centre, for the period 2010 to 2015. District level population data were extracted from the Ethiopia National and Regional Census Report. Spatial autocorrelation was explored using Moran's I statistic, Local Indicators of Spatial Association (LISA), and the Getis-Ord statistics. A multivariate Poisson regression model was developed with a conditional autoregressive (CAR) prior structure, and with posterior parameters estimated using a Bayesian Markov chain Monte Carlo (MCMC) simulation approach with Gibbs sampling, in WinBUGS.

Results: A total of 264 MDR-TB patients were included in the analysis. The overall crude incidence rate of MDR-TB for the six-year period was 3.0 cases per 100,000 population. The highest incidence rate was observed in Metema (21 cases per 100,000 population) and Humera (18 cases per 100,000 population) districts; whereas nine districts had zero cases. Spatial clustering of MDR-TB was observed in districts located in the Ethiopia-Sudan and Ethiopia-Eritrea border regions, where large numbers of seasonal migrants live. Spatial clustering of MDR-TB was positively associated with urbanization (RR: 1.02; 95%CI: 1.01, 1.04) and the percentage of men (RR: 1.58; 95% CI: 1.26, 1.99) in the districts; after accounting for these factors there was no residual spatial clustering.

Conclusion: Spatial clustering of MDR-TB, fully explained by demographic factors (urbanization and percent male), was detected in the border regions of northwest Ethiopia, in locations where seasonal migrants live and work. Cross-border initiatives including options for mobile TB treatment and follow up are important for the effective control of MDR-TB in the region.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0171800PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5300134PMC
September 2017

Visceral leishmaniasis treatment outcome and its determinants in northwest Ethiopia.

Epidemiol Health 2016 28;39:e2017001. Epub 2016 Dec 28.

Department of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.

Objectives: Poor treatment outcomes of visceral leishmaniasis (VL) are responsible for the high mortality rate of this condition in resource-limited settings such as Ethiopia. This study aimed to identify the proportion of poor VL treatment outcomes in northwest Ethiopia and to evaluate the determinants associated with poor outcomes.

Methods: A hospital-based retrospective study was conducted among 595 VL patients who were admitted to Kahsay Abera Hospital in northwest Ethiopia from October 2010 to April 2013. Data were entered into Epi Info version 7.0 and exported to SPSS version 20 for analysis. Bivariate and multivariate logistic regression models were fitted to identify the determinants of VL treatment outcomes. Adjusted odds ratio (aORs) with 95% confidence intervals (CIs) were used, and -values <0.05 were considered to indicate statistical significance.

Results: The proportion of poor treatment outcomes was 23.7%. Late diagnosis (≥29 days) (aOR, 4.34; 95% CI, 2.22 to 8.46), severe illness at admission (inability to walk) (aOR, 1.63; 95% CI, 1.06 to 2.40) and coinfection with VL and human immunodeficiency virus (HIV) (aOR, 2.72; 95% CI, 1.40 to 5.20) were found to be determinants of poor VL treatment outcomes.

Conclusions: Poor treatment outcomes, such as death, treatment failure, and non-adherence, were found to be common. Special attention must be paid to severely ill and VL/HIV-coinfected patients. To improve VL treatment outcomes, the early diagnosis and treatment of VL patients is recommended.
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http://dx.doi.org/10.4178/epih.e2017001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5343104PMC
March 2017

Prevalence and factors associated with overweight and obesity among private kindergarten school children in Bahirdar Town, Northwest Ethiopia: cross-sectional study.

BMC Res Notes 2017 Jan 4;10(1):22. Epub 2017 Jan 4.

Department of Human Nutrition, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.

Background: In Sub-Saharan Africa, most nutrition efforts have concentrated on under-nutrition in children. However, national surveys rarely report the high prevalence of overweight and obesity among children. Likewise, in Ethiopia there is growing recognition of the emergence of a "double-burden" of malnutrition, with under and over nutrition occurring simultaneously among children, especially allied with improvements in socio-economic conditions. Hence, the study aimed to assess the prevalence and factors associated with overweight and obesity among private kindergarten school children aged 3-6 years in Bahirdar town, Northwest Ethiopia.

Methods: A school-based cross sectional study was conducted in Bahirdar Town, northwest Ethiopia from August to September, 2015. Anthropometric measurements such as weight and height were taken from 462 private Kindergarten preschool children aged 3-6 years; socio-economic and demographic factors and feeding practices were collected by interviewing the, mothers or caregivers of the children. The z-score values for BMI-for-age of children were generated using Emergency Nutrition Assessment (ENA) for Standardized Monitoring and Assessment of Relief Transitions (SMART) 2011. Binary logistic regression model was used to identify factors associated with overweight and obesity in children. Odds ratio with 95% confidence interval (CI) was calculated to show the strength of association.

Results: The overall prevalence of overweight and obesity was 6.9% [95% CI 2.4, 11.4]. The prevalence of overweight and obesity were 4.1 and 2.8%, respectively. The odds of overweight and obesity was higher among children with high dietary diversity score (DDS) [AOR = 5.12, 95% CI 1.42, 18.47], family size of less than five [AOR = 4.76, 95% CI 1.84, 12.31] and a family having a private car [AOR = 3.43, 95% CI 1.02, 11.49].

Conclusions: The prevalence of overweight and obesity among private kindergarten preschool children in the study area was high. Interventions on improving feeding practice and doing physical activities are important for the control of overweight and obesity among children in urban settings.
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http://dx.doi.org/10.1186/s13104-016-2308-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5217453PMC
January 2017

Treatment outcomes in patients with multidrug-resistant tuberculosis in north-west Ethiopia.

Trop Med Int Health 2017 03 6;22(3):351-362. Epub 2017 Jan 6.

Research School of Population Health, Australian National University, Canberra, ACT, Australia.

Objective: Multidrug-resistant tuberculosis (MDR-TB) is an emerging public health problem in Ethiopia. The aim of this study was to assess MDR-TB treatment outcomes and determine predictors of poor treatment outcomes in north-west Ethiopia.

Methods: A retrospective cohort study was conducted using all MDR-TB patients who were enrolled at Gondar University Hospital since the establishment of the MDR-TB programme in 2010. A Cox proportional hazard model was used to identify the predictors of time to poor treatment outcomes, which were defined as death or treatment failure.

Results: Of the 242 patients who had complete records, 131 (54%) were cured, 23 (9%) completed treatment, 31 (13%) died, four (2%) experienced treatment failure, 27 (11%) were lost to follow-up, six (2%) transferred out, and 20 (8%) were still on treatment at the time of analysis. The overall cumulative probability survival of the patients at the end of treatment (which was 24 months in duration) was 80% (95% CI: 70%, 87%). The proportion of patients with poor treatment outcomes increased over time from 6% per person-year (PY) during 2010-2012, to 12% per PY during 2013-2015. The independent predictors of time to poor treatment outcome were being anaemic [AHR = 4.2; 95% CI: 1.1, 15.9] and being a farmer [AHR = 2.2; 95% CI: 1.0, 4.9].

Conclusions: Overall, in north-west Ethiopia, the MDR-TB treatment success rate was high. However, poor treatment outcomes have gradually increased since 2012. Being a farmer and being anaemic were associated with poor treatment outcomes. It would be beneficial to assess other risk factors that might affect treatment outcomes such as co-infection with malaria, poverty and other socio-economic and biological risk factors.
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http://dx.doi.org/10.1111/tmi.12826DOI Listing
March 2017

Predictors of treatment failure on second-line antiretroviral therapy among adults in northwest Ethiopia: a multicentre retrospective follow-up study.

BMJ Open 2016 12 8;6(12):e012537. Epub 2016 Dec 8.

Department of Epidemiology and Biostatistics, University of Gondar, College of Medicine and Health Sciences, Gondar, Ethiopia.

Background: The number of patients using second-line antiretroviral therapy (ART) has increased over time. In Ethiopia, 1.5% of HIV infected patients on ART are using a second-line regimen and little is known about its effect in this setting.

Objective: To estimate the rate and predictors of treatment failure on second-line ART among adults living with HIV in northwest Ethiopia.

Setting: An institution-based retrospective follow-up study was conducted at three tertiary hospitals in northwest Ethiopia from March to May 2015.

Participants: 356 adult patients participated and 198 (55.6%) were males. Individuals who were on second-line ART for at least 6 months of treatment were included and the data were collected by reviewing their records.

Primary Outcome Measure: The primary outcome was treatment failure defined as immunological failure, clinical failure, death, or lost to follow-up. To assess our outcome, we used the definitions of the WHO 2010 guideline.

Result: The mean±SD age of participants at switch was 36±8.9 years. The incidence rate of failure was 61.7/1000 person years. The probability of failure at the end of 12 and 24 months were 5.6% and 13.6%, respectively. Out of 67 total failures, 42 (62.7%) occurred in the first 2 years. The significant predictors of failure were found to be: WHO clinical stage IV at switch (adjusted HR (AHR) 2.1, 95% CI 1.1 to 4.1); CD4 count <100 cells/mm at switch (AHR 2.0, 95% CI 1.2 to 3.5); and weight change (AHR 0.92, 95% CI 0.88 to 0.95).

Conclusions: The rate of treatment failure was highest during the first 2 years of treatment. WHO clinical stage, CD4 count at switch, and change in weight were found to be predictors of treatment failure.
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http://dx.doi.org/10.1136/bmjopen-2016-012537DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5168604PMC
December 2016