Publications by authors named "George J Milne"

18 Publications

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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 Desyibelew Sagnik Dey Samath Dhamminda Dharmaratne Meghnath Dhimal Daniel Diaz Leila Doshmangir Andre R Duraes Laura Dwyer-Lindgren Lucas Earl Roya Ebrahimi Soheil Ebrahimpour Andem Effiong Aziz Eftekhari Elham Ehsani-Chimeh Iman El Sayed Maysaa El Sayed Zaki Maha El Tantawi Ziad El-Khatib Mohammad Hassan Emamian Shymaa Enany Sharareh Eskandarieh Oghenowede Eyawo Maha Ezalarab Mahbobeh Faramarzi Mohammad Fareed Roghiyeh Faridnia Andre Faro Ali Akbar Fazaeli Mehdi Fazlzadeh Netsanet Fentahun Seyed-Mohammad Fereshtehnejad João C Fernandes Irina Filip Florian Fischer Nataliya A Foigt Masoud Foroutan Joel Msafiri Francis Takeshi Fukumoto Nancy Fullman Silvano Gallus Destallem Gebremedhin Gebre Tsegaye Tewelde Gebrehiwot Gebreamlak Gebremedhn Gebremeskel Bradford D Gessner Birhanu Geta Peter W Gething Reza Ghadimi Keyghobad Ghadiri Mahsa Ghajarzadeh Ahmad Ghashghaee Paramjit Singh Gill Tiffany K Gill Nick Golding Nelson G M Gomes Philimon N Gona Sameer Vali Gopalani Giuseppe Gorini Bárbara 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 Keiyoro Grant Rodgers Kemp Roghayeh Khabiri Yousef Saleh Khader Morteza Abdullatif Khafaie Ejaz Ahmad Khan Junaid Khan Muhammad Shahzeb Khan Young-Ho Khang Khaled Khatab Amir Khater Mona M Khater Alireza Khatony Mohammad Khazaei Salman Khazaei Maryam Khazaei-Pool Jagdish Khubchandani Neda Kianipour Yun Jin Kim Ruth W Kimokoti Damaris K Kinyoki Adnan Kisa Sezer Kisa Tufa Kolola Soewarta Kosen Parvaiz A Koul Ai Koyanagi Moritz U G Kraemer Kewal Krishan Kris J Krohn Nuworza Kugbey G Anil Kumar Manasi Kumar Pushpendra Kumar Desmond Kuupiel Ben Lacey Sheetal D Lad Faris Hasan Lami Anders O Larsson Paul H Lee Mostafa Leili Aubrey J Levine Shanshan Li Lee-Ling Lim Stefan Listl Joshua Longbottom Jaifred Christian F Lopez Stefan Lorkowski Sameh Magdeldin Hassan Magdy Abd El Razek Muhammed Magdy Abd El Razek Azeem Majeed Afshin Maleki Reza Malekzadeh Deborah Carvalho Malta Abdullah A Mamun Navid Manafi Ana-Laura Manda Morteza Mansourian Francisco Rogerlândio Martins-Melo Anthony Masaka Benjamin 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

The cost-effectiveness of trivalent and quadrivalent influenza vaccination in communities in South Africa, Vietnam and Australia.

Vaccine 2018 02 17;36(7):997-1007. Epub 2018 Jan 17.

School of Computer Science and Software Engineering, University of Western Australia, Perth, Australia. Electronic address:

Background: To inform national healthcare authorities whether quadrivalent influenza vaccines (QIVs) provide better value for money than trivalent influenza vaccines (TIVs), we assessed the cost-effectiveness of TIV and QIV in low-and-middle income communities based in South Africa and Vietnam and contrasted these findings with those from a high-income community in Australia.

Methods: Individual based dynamic simulation models were interfaced with a health economic analysis model to estimate the cost-effectiveness of vaccinating 15% of the population with QIV or TIV in each community over the period 2003-2013. Vaccination was prioritized for HIV-infected individuals, before elderly aged 65+ years and young children. Country or region-specific data on influenza-strain circulation, clinical outcomes and costs were obtained from published sources. The societal perspective was used and outcomes were expressed in International$ (I$) per quality-adjusted life-year (QALY) gained.

Results: When compared with TIV, we found that QIV would provide a greater reduction in influenza-related morbidity in communities in South Africa and Vietnam as compared with Australia. The incremental cost-effectiveness ratio of QIV versus TIV was estimated at I$4183/QALY in South Africa, I$1505/QALY in Vietnam and I$80,966/QALY in Australia.

Conclusions: The cost-effectiveness of QIV varied between communities due to differences in influenza epidemiology, comorbidities, and unit costs. Whether TIV or QIV is the most cost-effective alternative heavily depends on influenza B burden among subpopulations targeted forvaccination in addition to country-specific willingness-to-pay thresholds and budgetary impact.
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http://dx.doi.org/10.1016/j.vaccine.2017.12.073DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5805858PMC
February 2018

Spatial Effects on the Multiplicity of Plasmodium falciparum Infections.

PLoS One 2016 6;11(10):e0164054. Epub 2016 Oct 6.

Population-Based Biology Division, Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia.

As malaria is being pushed back on many frontiers and global case numbers are declining, accurate measurement and prediction of transmission becomes increasingly difficult. Low transmission settings are characterised by high levels of spatial heterogeneity, which stands in stark contrast to the widely used assumption of spatially homogeneous transmission used in mathematical transmission models for malaria. In the present study an individual-based mathematical malaria transmission model that incorporates multiple parasite clones, variable human exposure and duration of infection, limited mosquito flight distance and most importantly geographically heterogeneous human and mosquito population densities was used to illustrate the differences between homogeneous and heterogeneous transmission assumptions when aiming to predict surrogate indicators of transmission intensity such as population parasite prevalence or multiplicity of infection (MOI). In traditionally highly malaria endemic regions where most of the population harbours malaria parasites, humans are often infected with multiple parasite clones. However, studies have shown also in areas with low overall parasite prevalence, infection with multiple parasite clones is a common occurrence. Mathematical models assuming homogeneous transmission between humans and mosquitoes cannot explain these observations. Heterogeneity of transmission can arise from many factors including acquired immunity, body size and occupational exposure. In this study, we show that spatial heterogeneity has a profound effect on predictions of MOI and parasite prevalence. We illustrate, that models assuming homogeneous transmission underestimate average MOI in low transmission settings when compared to field data and that spatially heterogeneous models predict stable transmission at much lower overall parasite prevalence. Therefore it is very important that models used to guide malaria surveillance and control strategies in low transmission and elimination settings take into account the spatial features of the specific target area, including human and mosquito vector distribution.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0164054PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5053403PMC
June 2017

Trivalent and quadrivalent influenza vaccination effectiveness in Australia and South Africa: results from a modelling study.

Influenza Other Respir Viruses 2016 07 8;10(4):324-32. Epub 2016 Feb 8.

Centre for Respiratory Disease and Meningitis, National Institute for Communicable Diseases, Johannesburg, South Africa.

Background: A modelling study was conducted to determine the effectiveness of trivalent (TIV) and quadrivalent (QIV) vaccination in South Africa and Australia.

Objectives: This study aimed to determine the potential benefits of alternative vaccination strategies which may depend on community-specific demographic and health characteristics.

Methods: Two influenza A and two influenza B strains were simulated using individual-based simulation models representing specific communities in South Africa and Australia over 11 years. Scenarios using TIV or QIV, with alternative prioritisation strategies and vaccine coverage levels, were evaluated using a country-specific health outcomes process.

Results: In South Africa, approximately 18% fewer deaths and hospitalisations would be expected to result from the use of QIV compared to TIV over the 11 modelled years (P = 0·031). In Australia, only 2% (P = 0·30) fewer deaths and hospitalisations would result. Vaccinating 2%, 5%, 15% or 20% of the population with TIV using a strategy of prioritising vulnerable age groups, including HIV-positive individuals, resulted in reductions in hospitalisations and mortality of at least 7%, 18%, 57% and 66%, respectively, in both communities.

Conclusions: The degree to which QIV can reduce health burden compared to TIV is strongly dependent on the number of years in which the influenza B lineage in the TIV matches the circulating B lineages. Assuming a moderate level of B cross-strain protection, TIV may be as effective as QIV. The choice of vaccination prioritisation has a greater impact than the QIV/TIV choice, with strategies targeting those most responsible for transmission being most effective.
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http://dx.doi.org/10.1111/irv.12367DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4910176PMC
July 2016

A spatial simulation model for dengue virus infection in urban areas.

BMC Infect Dis 2014 Aug 20;14:447. Epub 2014 Aug 20.

School of Computer Science and Software Engineering, The University of Western Australia, 35 Stirling Highway, Crawley, Perth, WA 6009, Australia.

Background: The World Health Organization estimates that the global number of dengue infections range between 80-100 million per year, with some studies estimating approximately three times higher numbers. Furthermore, the geographic range of dengue virus transmission is extending with the disease now occurring more frequently in areas such as southern Europe. Ae. aegypti, one of the most prominent dengue vectors, is endemic to the far north-east of Australia and the city of Cairns frequently experiences dengue outbreaks which sometimes lead to large epidemics.

Method: A spatially-explicit, individual-based mathematical model that accounts for the spread of dengue infection as a result of human movement and mosquito dispersion is presented. The model closely couples the four key sub-models necessary for representing the overall dynamics of the physical system, namely those describing mosquito population dynamics, human movement, virus transmission and vector control. Important features are the use of high quality outbreak data and mosquito trapping data for calibration and validation and a strategy to derive local mosquito abundance based on vegetation coverage and census data.

Results: The model has been calibrated using detailed 2003 dengue outbreak data from Cairns, together with census and mosquito trapping data, and is shown to realistically reproduce a further dengue outbreak. The simulation results replicating the 2008/2009 Cairns epidemic support several hypotheses (formulated previously) aimed at explaining the large-scale epidemic which occurred in 2008/2009; specifically, while warmer weather and increased human movement had only a small effect on the spread of the virus, a shorter virus strain-specific extrinsic incubation time can explain the observed explosive outbreak of 2008/2009.

Conclusion: The proof-of-concept simulation model described in this study has potential as a tool for understanding factors contributing to dengue spread as well as planning and optimizing dengue control, including reducing the Ae. aegypti vector population and for estimating the effectiveness and cost-effectiveness of future vaccination programmes. This model could also be applied to other vector borne viral diseases such as chikungunya, also spread by Ae. aegypti and, by re-parameterisation of the vector sub-model, to dengue and chikungunya viruses spread by Aedes albopictus.
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http://dx.doi.org/10.1186/1471-2334-14-447DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4152583PMC
August 2014

A spatial simulation model for the dispersal of the bluetongue vector Culicoides brevitarsis in Australia.

PLoS One 2014 8;9(8):e104646. Epub 2014 Aug 8.

School of Computer Science and Software Engineering, University of Western Australia, Crawley, Western Australia, Australia.

Background: The spread of Bluetongue virus (BTV) among ruminants is caused by movement of infected host animals or by movement of infected Culicoides midges, the vector of BTV. Biologically plausible models of Culicoides dispersal are necessary for predicting the spread of BTV and are important for planning control and eradication strategies.

Methods: A spatially-explicit simulation model which captures the two underlying population mechanisms, population dynamics and movement, was developed using extensive data from a trapping program for C. brevitarsis on the east coast of Australia. A realistic midge flight sub-model was developed and the annual incursion and population establishment of C. brevitarsis was simulated. Data from the literature was used to parameterise the model.

Results: The model was shown to reproduce the spread of C. brevitarsis southwards along the east Australian coastline in spring, from an endemic population to the north. Such incursions were shown to be reliant on wind-dispersal; Culicoides midge active flight on its own was not capable of achieving known rates of southern spread, nor was re-emergence of southern populations due to overwintering larvae. Data from midge trapping programmes were used to qualitatively validate the resulting simulation model.

Conclusions: The model described in this paper is intended to form the vector component of an extended model that will also include BTV transmission. A model of midge movement and population dynamics has been developed in sufficient detail such that the extended model may be used to evaluate the timing and extent of BTV outbreaks. This extended model could then be used as a platform for addressing the effectiveness of spatially targeted vaccination strategies or animal movement bans as BTV spread mitigation measures, or the impact of climate change on the risk and extent of outbreaks. These questions involving incursive Culicoides spread cannot be simply addressed with non-spatial models.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0104646PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4126746PMC
December 2015

A model-based economic analysis of pre-pandemic influenza vaccination cost-effectiveness.

BMC Infect Dis 2014 May 16;14:266. Epub 2014 May 16.

School of Computer Science and Software Engineering, The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia.

Background: A vaccine matched to a newly emerged pandemic influenza virus would require a production time of at least 6 months with current proven techniques, and so could only be used reactively after the peak of the pandemic. A pre-pandemic vaccine, although probably having lower efficacy, could be produced and used pre-emptively. While several previous studies have investigated the cost effectiveness of pre-emptive vaccination strategies, they have not been directly compared to realistic reactive vaccination strategies.

Methods: An individual-based simulation model of ~30,000 people was used to examine a pre-emptive vaccination strategy, assuming vaccination conducted prior to a pandemic using a low-efficacy vaccine. A reactive vaccination strategy, assuming a 6-month delay between pandemic emergence and availability of a high-efficacy vaccine, was also modelled. Social distancing and antiviral interventions were examined in combination with these alternative vaccination strategies. Moderate and severe pandemics were examined, based on estimates of transmissibility and clinical severity of the 1957 and 1918 pandemics respectively, and the cost effectiveness of each strategy was evaluated.

Results: Provided that a pre-pandemic vaccine achieved at least 30% efficacy, pre-emptive vaccination strategies were found to be more cost effective when compared to reactive vaccination strategies. Reactive vaccination coupled with sustained social distancing and antiviral interventions was found to be as effective at saving lives as pre-emptive vaccination coupled with limited duration social distancing and antiviral use, with both strategies saving approximately 420 life-years per 10,000 population for a moderate pandemic with a basic reproduction number of 1.9 and case fatality rate of 0.25%. Reactive vaccination was however more costly due to larger productivity losses incurred by sustained social distancing, costing $8 million per 10,000 population ($19,074/LYS) versus $6.8 million per 10,000 population ($15,897/LYS) for a pre-emptive vaccination strategy. Similar trends were observed for severe pandemics.

Conclusions: Compared to reactive vaccination, pre-emptive strategies would be more effective and more cost effective, conditional on the pre-pandemic vaccine being able to achieve a certain level of coverage and efficacy. Reactive vaccination strategies exist which are as effective at mortality reduction as pre-emptive strategies, though they are less cost effective.
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http://dx.doi.org/10.1186/1471-2334-14-266DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4045999PMC
May 2014

Trends in parameterization, economics and host behaviour in influenza pandemic modelling: a review and reporting protocol.

Emerg Themes Epidemiol 2013 May 7;10(1). Epub 2013 May 7.

Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore.

Background: The volume of influenza pandemic modelling studies has increased dramatically in the last decade. Many models incorporate now sophisticated parameterization and validation techniques, economic analyses and the behaviour of individuals.

Methods: We reviewed trends in these aspects in models for influenza pandemic preparedness that aimed to generate policy insights for epidemic management and were published from 2000 to September 2011, i.e. before and after the 2009 pandemic.

Results: We find that many influenza pandemics models rely on parameters from previous modelling studies, models are rarely validated using observed data and are seldom applied to low-income countries. Mechanisms for international data sharing would be necessary to facilitate a wider adoption of model validation. The variety of modelling decisions makes it difficult to compare and evaluate models systematically.

Conclusions: We propose a model Characteristics, Construction, Parameterization and Validation aspects protocol (CCPV protocol) to contribute to the systematisation of the reporting of models with an emphasis on the incorporation of economic aspects and host behaviour. Model reporting, as already exists in many other fields of modelling, would increase confidence in model results, and transparency in their assessment and comparison.
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http://dx.doi.org/10.1186/1742-7622-10-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3666982PMC
May 2013

The cost effectiveness of pandemic influenza interventions: a pandemic severity based analysis.

PLoS One 2013 9;8(4):e61504. Epub 2013 Apr 9.

Simulation and Modelling Research Unit, University of Western Australia, Perth, Australia.

Background: The impact of a newly emerged influenza pandemic will depend on its transmissibility and severity. Understanding how these pandemic features impact on the effectiveness and cost effectiveness of alternative intervention strategies is important for pandemic planning.

Methods: A cost effectiveness analysis of a comprehensive range of social distancing and antiviral drug strategies intended to mitigate a future pandemic was conducted using a simulation model of a community of ∼30,000 in Australia. Six pandemic severity categories were defined based on case fatality ratio (CFR), using data from the 2009/2010 pandemic to relate hospitalisation rates to CFR.

Results: Intervention strategies combining school closure with antiviral treatment and prophylaxis are the most cost effective strategies in terms of cost per life year saved (LYS) for all severity categories. The cost component in the cost per LYS ratio varies depending on pandemic severity: for a severe pandemic (CFR of 2.5%) the cost is ∼$9 k per LYS; for a low severity pandemic (CFR of 0.1%) this strategy costs ∼$58 k per LYS; for a pandemic with very low severity similar to the 2009 pandemic (CFR of 0.03%) the cost is ∼$155 per LYS. With high severity pandemics (CFR >0.75%) the most effective attack rate reduction strategies are also the most cost effective. During low severity pandemics costs are dominated by productivity losses due to illness and social distancing interventions, while for high severity pandemics costs are dominated by hospitalisation costs and productivity losses due to death.

Conclusions: The most cost effective strategies for mitigating an influenza pandemic involve combining sustained social distancing with the use of antiviral agents. For low severity pandemics the most cost effective strategies involve antiviral treatment, prophylaxis and short durations of school closure; while these are cost effective they are less effective than other strategies in reducing the infection rate.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0061504PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3621766PMC
October 2013

Pandemic influenza in Papua New Guinea: a modelling study comparison with pandemic spread in a developed country.

BMJ Open 2013 Mar 26;3(3). Epub 2013 Mar 26.

School of Computer Science and Software Engineering, University of Western Australia, Perth, Western Australia, Australia.

Objectives: The possible occurrence of a highly pathogenic influenza strain is of concern to health authorities worldwide. It is known that during past influenza pandemics developing countries have experienced considerably higher death rates compared with developed countries. Furthermore, many developing countries lack appropriate pandemic preparedness plans. Mathematical modelling studies to guide the development of such plans are largely focused on predicting pandemic influenza spread in developed nations. However, intervention strategies shown by modelling studies to be highly effective for developed countries give limited guidance as to the impact which an influenza pandemic may have on low-income countries given different demographics and resource constraints. To address this, an individual-based model of a Papua New Guinean (PNG) community was created and used to simulate the spread of a novel influenza strain. The results were compared with those obtained from a comparable Australian model.

Design: A modelling study.

Setting: The towns of Madang in PNG (population ∼35 000) and Albany (population ∼30 000) in Australia.

Outcome Measures: Daily and cumulative illness attack rates in both models following introduction of a novel influenza strain into a naive population, for an unmitigated scenario and two social distancing intervention scenarios.

Results: The unmitigated scenario indicated an approximately 50% higher attack rate in PNG compared with the Australian model. The two social distancing-based interventions strategies were 60-70% less effective in a PNG setting compared with an Australian setting.

Conclusions: This study provides further evidence that an influenza pandemic occurring in a low-income country such as PNG may have a greater impact than one occurring in a developed country, and that PNG-feasible interventions may be substantially less effective. The larger average household size in PNG, the larger proportion of the population under 18 and greater community-wide contact all contribute to this feature.
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http://dx.doi.org/10.1136/bmjopen-2012-002518DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3612822PMC
March 2013

Economic analysis of pandemic influenza mitigation strategies for five pandemic severity categories.

BMC Public Health 2013 Mar 8;13:211. Epub 2013 Mar 8.

School of Computer Science and Software Engineering, University of Western Australia, Perth, Western Australia, Australia.

Background: The threat of emergence of a human-to-human transmissible strain of highly pathogenic influenza A(H5N1) is very real, and is reinforced by recent results showing that genetically modified A(H5N1) may be readily transmitted between ferrets. Public health authorities are hesitant in introducing social distancing interventions due to societal disruption and productivity losses. This study estimates the effectiveness and total cost (from a societal perspective, with a lifespan time horizon) of a comprehensive range of social distancing and antiviral drug strategies, under a range of pandemic severity categories.

Methods: An economic analysis was conducted using a simulation model of a community of ~30,000 in Australia. Data from the 2009 pandemic was used to derive relationships between the Case Fatality Rate (CFR) and hospitalization rates for each of five pandemic severity categories, with CFR ranging from 0.1% to 2.5%.

Results: For a pandemic with basic reproduction number R0 = 1.8, adopting no interventions resulted in total costs ranging from $441 per person for a pandemic at category 1 (CFR 0.1%) to $8,550 per person at category 5 (CFR 2.5%). For severe pandemics of category 3 (CFR 0.75%) and greater, a strategy combining antiviral treatment and prophylaxis, extended school closure and community contact reduction resulted in the lowest total cost of any strategy, costing $1,584 per person at category 5. This strategy was highly effective, reducing the attack rate to 5%. With low severity pandemics costs are dominated by productivity losses due to illness and social distancing interventions, whereas higher severity pandemic costs are dominated by healthcare costs and costs arising from productivity losses due to death.

Conclusions: For pandemics in high severity categories the strategies with the lowest total cost to society involve rigorous, sustained social distancing, which are considered unacceptable for low severity pandemics due to societal disruption and cost.
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http://dx.doi.org/10.1186/1471-2458-13-211DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3606600PMC
March 2013

Vaccination strategies for future influenza pandemics: a severity-based cost effectiveness analysis.

BMC Infect Dis 2013 Feb 11;13:81. Epub 2013 Feb 11.

School of Computer Science and Software Engineering, University of Western Australia, Stirling Highway, Crawley, Western Australia 6009, Australia.

Background: A critical issue in planning pandemic influenza mitigation strategies is the delay between the arrival of the pandemic in a community and the availability of an effective vaccine. The likely scenario, born out in the 2009 pandemic, is that a newly emerged influenza pandemic will have spread to most parts of the world before a vaccine matched to the pandemic strain is produced. For a severe pandemic, additional rapidly activated intervention measures will be required if high mortality rates are to be avoided.

Methods: A simulation modelling study was conducted to examine the effectiveness and cost effectiveness of plausible combinations of social distancing, antiviral and vaccination interventions, assuming a delay of 6-months between arrival of an influenza pandemic and first availability of a vaccine. Three different pandemic scenarios were examined; mild, moderate and extreme, based on estimates of transmissibility and pathogenicity of the 2009, 1957 and 1918 influenza pandemics respectively. A range of different durations of social distancing were examined, and the sensitivity of the results to variation in the vaccination delay, ranging from 2 to 6 months, was analysed.

Results: Vaccination-only strategies were not cost effective for any pandemic scenario, saving few lives and incurring substantial vaccination costs. Vaccination coupled with long duration social distancing, antiviral treatment and antiviral prophylaxis was cost effective for moderate pandemics and extreme pandemics, where it saved lives while simultaneously reducing the total pandemic cost. Combined social distancing and antiviral interventions without vaccination were significantly less effective, since without vaccination a resurgence in case numbers occurred as soon as social distancing interventions were relaxed. When social distancing interventions were continued until at least the start of the vaccination campaign, attack rates and total costs were significantly lower, and increased rates of vaccination further improved effectiveness and cost effectiveness.

Conclusions: The effectiveness and cost effectiveness consequences of the time-critical interplay of pandemic dynamics, vaccine availability and intervention timing has been quantified. For moderate and extreme pandemics, vaccination combined with rapidly activated antiviral and social distancing interventions of sufficient duration is cost effective from the perspective of life years saved.
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http://dx.doi.org/10.1186/1471-2334-13-81DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3637125PMC
February 2013

Cost-effective strategies for mitigating a future influenza pandemic with H1N1 2009 characteristics.

PLoS One 2011 8;6(7):e22087. Epub 2011 Jul 8.

School of Computer Science and Software Engineering, University of Western Australia, Crawley, Western Australia, Australia.

Background: We performed an analysis of the cost-effectiveness of pandemic intervention strategies using a detailed, individual-based simulation model of a community in Australia together with health outcome data of infected individuals gathered during 2009-2010. The aim was to examine the cost-effectiveness of a range of interventions to determine the most cost-effective strategies suitable for a future pandemic with H1N1 2009 characteristics.

Methodology/principal Findings: Using transmissibility, age-stratified attack rates and health outcomes determined from H1N1 2009 data, we determined that the most cost-effective strategies involved treatment and household prophylaxis using antiviral drugs combined with limited duration school closure, with costs ranging from $632 to $777 per case prevented. When school closure was used as a sole intervention we found the use of limited duration school closure to be significantly more cost-effective compared to continuous school closure, a result with applicability to countries with limited access to antiviral drugs. Other social distancing strategies, such as reduced workplace attendance, were found to be costly due to productivity losses.

Conclusion: The mild severity (low hospitalisation and case fatality rates) and low transmissibility of H1N1 2009 meant that health treatment costs were dominated by the higher productivity losses arising from workplace absence due to illness and childcare requirements following school closure. Further analysis for higher transmissibility but with the same, mild severity had no effect on the overall findings.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0022087PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3132288PMC
October 2011

The impact of case diagnosis coverage and diagnosis delays on the effectiveness of antiviral strategies in mitigating pandemic influenza A/H1N1 2009.

PLoS One 2010 Nov 3;5(11):e13797. Epub 2010 Nov 3.

School of Computer Science and Software Engineering, University of Western Australia, Crawley, Australia.

Background: Neuraminidase inhibitors were used to reduce the transmission of pandemic influenza A/H1N1 2009 at the early stages of the 2009/2010 pandemic. Policies for diagnosis of influenza for the purposes of antiviral intervention differed markedly between and within countries, leading to differences in the timing and scale of antiviral usage.

Methodology/principal Findings: The impact of the percentage of symptomatic infected individuals who were diagnosed, and of delays to diagnosis, for three antiviral intervention strategies (each with and without school closure) were determined using a simulation model of an Australian community. Epidemic characteristics were based on actual data from the A/H1N1 2009 pandemic including reproduction number, serial interval and age-specific infection rate profile. In the absence of intervention an illness attack rate (AR) of 24.5% was determined from an estimated R(0) of 1.5; this was reduced to 21%, 16.5% or 13% by treatment-only, treatment plus household prophylaxis, or treatment plus household plus extended prophylaxis antiviral interventions respectively, assuming that diagnosis occurred 24 hours after symptoms arose and that 50% of symptomatic cases were diagnosed. If diagnosis occurred without delay, ARs decreased to 17%, 12.2% or 8.8% respectively. If 90% of symptomatic cases were diagnosed (with a 24 hour delay), ARs decreased to 17.8%, 11.1% and 7.6%, respectively.

Conclusion: The ability to rapidly diagnose symptomatic cases and to diagnose a high proportion of cases was shown to improve the effectiveness of all three antiviral strategies. For epidemics with R(0)< = 1.5 our results suggest that when the case diagnosis coverage exceeds ∼70% the size of the antiviral stockpile required to implement the extended prophylactic strategy decreases. The addition of at least four weeks of school closure was found to further reduce cumulative and peak attack rates and the size of the required antiviral stockpile.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0013797PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2972206PMC
November 2010

Developing guidelines for school closure interventions to be used during a future influenza pandemic.

BMC Infect Dis 2010 Jul 27;10:221. Epub 2010 Jul 27.

School of Computer Science and Software Engineering, University of Western Australia, Perth, Australia.

Background: The A/H1N1 2009 influenza pandemic revealed that operational issues of school closure interventions, such as when school closure should be initiated (activation trigger), how long schools should be closed (duration) and what type of school closure should be adopted, varied greatly between and within countries. Computer simulation can be used to examine school closure intervention strategies in order to inform public health authorities as they refine school closure guidelines in light of experience with the A/H1N1 2009 pandemic.

Methods: An individual-based simulation model was used to investigate the effectiveness of school closure interventions for influenza pandemics with R0 of 1.5, 2.0 and 2.5. The effectiveness of individual school closure and simultaneous school closure were analyzed for 2, 4 and 8 weeks closure duration, with a daily diagnosed case based intervention activation trigger scheme. The effectiveness of combining antiviral drug treatment and household prophyaxis with school closure was also investigated.

Results: Illness attack rate was reduced from 33% to 19% (14% reduction in overall attack rate) by 8 weeks school closure activating at 30 daily diagnosed cases in the community for an influenza pandemic with R0 = 1.5; when combined with antivirals a 19% (from 33% to 14%) reduction in attack rate was obtained. For R(0) > or = 2.0, school closure would be less effective. An 8 weeks school closure strategy gives 9% (from 50% to 41%) and 4% (from 59% to 55%) reduction in attack rate for R(0) = 2.0 and 2.5 respectively; however, school closure plus antivirals would give a significant reduction (approximately 15%) in over all attack rate. The results also suggest that an individual school closure strategy would be more effective than simultaneous school closure.

Conclusions: Our results indicate that the particular school closure strategy to be adopted depends both on the disease severity, which will determine the duration of school closure deemed acceptable, and its transmissibility. For epidemics with a low transmissibility (R(0) < 2.0) and/or mild severity, individual school closures should begin once a daily community case count is exceeded. For a severe, highly transmissible epidemic (R(0) > or = 2.0), long duration school closure should begin as soon as possible and be combined with other interventions.
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http://dx.doi.org/10.1186/1471-2334-10-221DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2915996PMC
July 2010

Analysis of the effectiveness of interventions used during the 2009 A/H1N1 influenza pandemic.

BMC Public Health 2010 Mar 29;10:168. Epub 2010 Mar 29.

School of Computer Science and Software Engineering, University of Western Australia, Perth, Australia.

Background: Following the emergence of the A/H1N1 2009 influenza pandemic, public health interventions were activated to lessen its potential impact. Computer modelling and simulation can be used to determine the potential effectiveness of the social distancing and antiviral drug therapy interventions that were used at the early stages of the pandemic, providing guidance to public health policy makers as to intervention strategies in future pandemics involving a highly pathogenic influenza strain.

Methods: An individual-based model of a real community with a population of approximately 30,000 was used to determine the impact of alternative interventions strategies, including those used in the initial stages of the 2009 pandemic. Different interventions, namely school closure and antiviral strategies, were simulated in isolation and in combination to form different plausible scenarios. We simulated epidemics with reproduction numbers R0 of 1.5, which aligns with estimates in the range 1.4-1.6 determined from the initial outbreak in Mexico.

Results: School closure of 1 week was determined to have minimal effect on reducing overall illness attack rate. Antiviral drug treatment of 50% of symptomatic cases reduced the attack rate by 6.5%, from an unmitigated rate of 32.5% to 26%. Treatment of diagnosed individuals combined with additional household prophylaxis reduced the final attack rate to 19%. Further extension of prophylaxis to close contacts (in schools and workplaces) further reduced the overall attack rate to 13% and reduced the peak daily illness rate from 120 to 22 per 10,000 individuals. We determined the size of antiviral stockpile required; the ratio of the required number of antiviral courses to population was 13% for the treatment-only strategy, 25% for treatment and household prophylaxis and 40% for treatment, household and extended prophylaxis. Additional simulations suggest that coupling school closure with the antiviral strategies further reduces epidemic impact.

Conclusions: These results suggest that the aggressive use of antiviral drugs together with extended school closure may substantially slow the rate of influenza epidemic development. These strategies are more rigorous than those actually used during the early stages of the relatively mild 2009 pandemic, and are appropriate for future pandemics that have high morbidity and mortality rates.
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http://dx.doi.org/10.1186/1471-2458-10-168DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2853510PMC
March 2010

Simulation suggests that rapid activation of social distancing can arrest epidemic development due to a novel strain of influenza.

BMC Public Health 2009 Apr 29;9:117. Epub 2009 Apr 29.

School of Computer Science and Software Engineering, University of Western Australia, Perth, WA, Australia.

Background: Social distancing interventions such as school closure and prohibition of public gatherings are present in pandemic influenza preparedness plans. Predicting the effectiveness of intervention strategies in a pandemic is difficult. In the absence of other evidence, computer simulation can be used to help policy makers plan for a potential future influenza pandemic. We conducted simulations of a small community to determine the magnitude and timing of activation that would be necessary for social distancing interventions to arrest a future pandemic.

Methods: We used a detailed, individual-based model of a real community with a population of approximately 30,000. We simulated the effect of four social distancing interventions: school closure, increased isolation of symptomatic individuals in their household, workplace nonattendance, and reduction of contact in the wider community. We simulated each of the intervention measures in isolation and in several combinations; and examined the effect of delays in the activation of interventions on the final and daily attack rates.

Results: For an epidemic with an R0 value of 1.5, a combination of all four social distancing measures could reduce the final attack rate from 33% to below 10% if introduced within 6 weeks from the introduction of the first case. In contrast, for an R0 of 2.5 these measures must be introduced within 2 weeks of the first case to achieve a similar reduction; delays of 2, 3 and 4 weeks resulted in final attack rates of 7%, 21% and 45% respectively. For an R0 of 3.5 the combination of all four measures could reduce the final attack rate from 73% to 16%, but only if introduced without delay; delays of 1, 2 or 3 weeks resulted in final attack rates of 19%, 35% or 63% respectively. For the higher R0 values no single measure has a significant impact on attack rates.

Conclusion: Our results suggest a critical role of social distancing in the potential control of a future pandemic and indicate that such interventions are capable of arresting influenza epidemic development, but only if they are used in combination, activated without delay and maintained for a relatively long period.
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http://dx.doi.org/10.1186/1471-2458-9-117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2680828PMC
April 2009

A small community model for the transmission of infectious diseases: comparison of school closure as an intervention in individual-based models of an influenza pandemic.

PLoS One 2008 23;3(12):e4005. Epub 2008 Dec 23.

School of Computer Science and Software Engineering, The University of Western Australia, Crawley, Western Australia, Australia.

Background: In the absence of other evidence, modelling has been used extensively to help policy makers plan for a potential future influenza pandemic.

Method: We have constructed an individual based model of a small community in the developed world with detail down to exact household structure obtained from census collection datasets and precise simulation of household demographics, movement within the community and individual contact patterns. We modelled the spread of pandemic influenza in this community and the effect on daily and final attack rates of four social distancing measures: school closure, increased case isolation, workplace non-attendance and community contact reduction. We compared the modelled results of final attack rates in the absence of any interventions and the effect of school closure as a single intervention with other published individual based models of pandemic influenza in the developed world.

Results: We showed that published individual based models estimate similar final attack rates over a range of values for R(0) in a pandemic where no interventions have been implemented; that multiple social distancing measures applied early and continuously can be very effective in interrupting transmission of the pandemic virus for R(0) values up to 2.5; and that different conclusions reached on the simulated benefit of school closure in published models appear to result from differences in assumptions about the timing and duration of school closure and flow-on effects on other social contacts resulting from school closure.

Conclusion: Models of the spread and control of pandemic influenza have the potential to assist policy makers with decisions about which control strategies to adopt. However, attention needs to be given by policy makers to the assumptions underpinning both the models and the control strategies examined.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0004005PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2602849PMC
February 2009