Publications by authors named "Graham F Medley"

103 Publications

Implication of backward contact tracing in the presence of overdispersed transmission in COVID-19 outbreaks.

Wellcome Open Res 2020 31;5:239. Epub 2021 Mar 31.

Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.

Contact tracing has the potential to control outbreaks without the need for stringent physical distancing policies, e.g. civil lockdowns. Unlike forward contact tracing, backward contact tracing identifies the source of newly detected cases. This approach is particularly valuable when there is high individual-level variation in the number of secondary transmissions (overdispersion). By using a simple branching process model, we explored the potential of combining backward contact tracing with more conventional forward contact tracing for control of COVID-19. We estimated the typical size of clusters that can be reached by backward tracing and simulated the incremental effectiveness of combining backward tracing with conventional forward tracing. Across ranges of parameter values consistent with dynamics of SARS-CoV-2, backward tracing is expected to identify a primary case generating 3-10 times more infections than a randomly chosen case, typically increasing the proportion of subsequent cases averted by a factor of 2-3. The estimated number of cases averted by backward tracing became greater with a higher degree of overdispersion. Backward contact tracing can be an effective tool for outbreak control, especially in the presence of overdispersion as is observed with SARS-CoV-2.
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http://dx.doi.org/10.12688/wellcomeopenres.16344.3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610176.3PMC
March 2021

SCHISTOX: An individual based model for the epidemiology and control of schistosomiasis.

Infect Dis Model 2021 4;6:438-447. Epub 2021 Feb 4.

Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom.

A stochastic individual based model, SCHISTOX, has been developed for the study of schistosome transmission dynamics and the impact of control by mass drug administration. More novel aspects that can be investigated include individual level adherence and access to treatment, multiple communities, human sex population dynamics, and implementation of a potential vaccine. Many of the model parameters have been estimated within previous studies and have been shown to vary between communities, such as the age-specific contact rates governing the age profiles of infection. However, uncertainty remains as there are wide ranges for certain parameter values and a few remain relatively unknown. We analyse the model dynamics by parameterizing it with published parameter values. We also discuss the development of SCHISTOX in the form of a publicly available open-source GitHub repository. The next key development stage involves validating the model by calibrating to epidemiological data.
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http://dx.doi.org/10.1016/j.idm.2021.01.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7897994PMC
February 2021

Costs and outcomes of active and passive case detection for visceral leishmaniasis (Kala-Azar) to inform elimination strategies in Bihar, India.

PLoS Negl Trop Dis 2021 Feb 3;15(2):e0009129. Epub 2021 Feb 3.

Department of Global Health and Development, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom.

Background: Effective case identification strategies are fundamental to capturing the remaining visceral leishmaniasis (VL) cases in India. To inform government strategies to reach and sustain elimination benchmarks, this study presents costs of active- and passive- case detection (ACD and PCD) strategies used in India's most VL-endemic state, Bihar, with a focus on programme outcomes stratified by district-level incidence.

Methods: Expenditure analysis was complemented by onsite micro-costing to compare the cost of PCD in hospitals alongside index case-based ACD and a combination of blanket (house-to-house) and camp ACD from January to December 2018. From the provider's perspective, a cost analysis evaluated the overall programme cost of each activity, the cost per case detected, and the cost of scaling up ACD.

Results: During 2018, index case-based ACD, blanket and camp ACD, and PCD reported 1,497, 131, and 1,983 VL-positive cases at a unit cost of $522.81, $4,186.81, and $246.79, respectively. In high endemic districts, more VL cases were identified through PCD while in meso- and low-endemic districts more cases were identified through ACD. The cost of scaling up ACD to identify 3,000 additional cases ranged from $1.6-4 million, depending on the extent to which blanket and camp ACD was relied upon.

Conclusion: Cost per VL test conducted (rather than VL-positive case identified) may be a better metric estimating unit costs to scale up ACD in Bihar. As more VL cases were identified in meso-and low-endemic districts through ACD than PCD, health authorities in India should consider bolstering ACD in these areas. Blanket and camp ACD identified fewer cases at a higher unit cost than index case-based ACD. However, the value of detecting additional VL cases early outweighs long-term costs for reaching and sustaining VL elimination benchmarks in India.
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http://dx.doi.org/10.1371/journal.pntd.0009129DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7886142PMC
February 2021

Towards Evidence-based Control of Opisthorchis viverrini.

Trends Parasitol 2021 Jan 27. Epub 2021 Jan 27.

Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford, OX3 7LF, UK.

Transmission of the carcinogenic liver fluke Opisthorchis viverrini is ongoing across Southeast Asia. Endemic countries within the region are in different stages of achieving control. However, evidence on which interventions are the most effective for reducing parasite transmission, and the resulting liver cancer, is currently lacking. Quantitative modelling can be used to evaluate different control measures against O. viverrini and assist the design of clinical trials. In this article we evaluate the epidemiological parameters that underpin models of O. viverrini and the data necessary for their estimation, with the aim of developing evidence-based strategies for parasite control at a national or regional level.
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http://dx.doi.org/10.1016/j.pt.2020.12.007DOI Listing
January 2021

Integrating epidemiological and genetic data with different sampling intensities into a dynamic model of respiratory syncytial virus transmission.

Sci Rep 2021 Jan 14;11(1):1463. Epub 2021 Jan 14.

Centre for Mathematical Modelling of Infectious Disease and Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, WC1H 9SH, UK.

Respiratory syncytial virus (RSV) is responsible for a significant burden of severe acute lower respiratory tract illness in children under 5 years old; particularly infants. Prior to rolling out any vaccination program, identification of the source of infant infections could further guide vaccination strategies. We extended a dynamic model calibrated at the individual host level initially fit to social-temporal data on shedding patterns to include whole genome sequencing data available at a lower sampling intensity. The study population was 493 individuals (55 aged < 1 year) distributed across 47 households, observed through one RSV season in coastal Kenya. We found that 58/97 (60%) of RSV-A and 65/125 (52%) of RSV-B cases arose from infection probably occurring within the household. Nineteen (45%) infant infections appeared to be the result of infection by other household members, of which 13 (68%) were a result of transmission from a household co-occupant aged between 2 and 13 years. The applicability of genomic data in studies of transmission dynamics is highly context specific; influenced by the question, data collection protocols and pathogen under investigation. The results further highlight the importance of pre-school and school-aged children in RSV transmission, particularly the role they play in directly infecting the household infant. These age groups are a potential RSV vaccination target group.
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http://dx.doi.org/10.1038/s41598-021-81078-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7809427PMC
January 2021

Individual and community-level benefits of PrEP in western Kenya and South Africa: Implications for population prioritization of PrEP provision.

PLoS One 2020 31;15(12):e0244761. Epub 2020 Dec 31.

Institute for Disease Modeling, Seattle, WA, United States of America.

Background: Pre-exposure prophylaxis (PrEP) is highly effective in preventing HIV and has the potential to significantly impact the HIV epidemic. Given limited resources for HIV prevention, identifying PrEP provision strategies that maximize impact is critical.

Methods: We used a stochastic individual-based network model to evaluate the direct (infections prevented among PrEP users) and indirect (infections prevented among non-PrEP users as a result of PrEP) benefits of PrEP, the person-years of PrEP required to prevent one HIV infection, and the community-level impact of providing PrEP to populations defined by gender and age in western Kenya and South Africa. We examined sensitivity of results to scale-up of antiretroviral therapy (ART) and voluntary medical male circumcision (VMMC) by comparing two scenarios: maintaining current coverage ("status quo") and rapid scale-up to meet programmatic targets ("fast-track").

Results: The community-level impact of PrEP was greatest among women aged 15-24 due to high incidence, while PrEP use among men aged 15-24 yielded the highest proportion of indirect infections prevented in the community. These indirect infections prevented continue to increase over time (western Kenya: 0.4-5.5 (status quo); 0.4-4.9 (fast-track); South Africa: 0.5-1.8 (status quo); 0.5-3.0 (fast-track)) relative to direct infections prevented among PrEP users. The number of person-years of PrEP needed to prevent one HIV infection was lower (59 western Kenya and 69 in South Africa in the status quo scenario; 201 western Kenya and 87 in South Africa in the fast-track scenario) when PrEP was provided only to women compared with only to men over time horizons of up to 5 years, as the indirect benefits of providing PrEP to men accrue in later years.

Conclusions: Providing PrEP to women aged 15-24 prevents the greatest number of HIV infections per person-year of PrEP, but PrEP provision for young men also provides indirect benefits to women and to the community overall. This finding supports existing policies that prioritize PrEP use for young women, while also illuminating the community-level benefits of PrEP availability for men when resources permit.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0244761PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775042PMC
March 2021

Herd immunity confusion.

Authors:
Graham F Medley

Lancet 2020 11 22;396(10263):1634-1635. Epub 2020 Oct 22.

London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK. Electronic address:

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http://dx.doi.org/10.1016/S0140-6736(20)32167-XDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7581340PMC
November 2020

Time to Scale Up Preexposure Prophylaxis Beyond the Highest-Risk Populations? Modeling Insights From High-Risk Women in Sub-Saharan Africa.

Sex Transm Dis 2020 11;47(11):767-777

From the Department of Global Health and Development, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine.

Objectives: New HIV infections remain higher in women than men in sub-Saharan Africa. Preexposure prophylaxis (PrEP) is an effective HIV prevention measure, currently prioritized for those at highest risk, such as female sex workers (FSWs), for whom it is most cost-effective. However, the greatest number of HIV infections in sub-Saharan Africa occurs in women in the general population. As countries consider wider PrEP scale-up, there is a need to weigh the population-level impact, cost, and relative cost-effectiveness to inform priority setting.

Methods: We developed mathematical models of HIV risk to women and derived tools to highlight key considerations for PrEP programming. The models were fitted to South Africa, Zimbabwe, and Kenya, spanning a range of HIV burden in sub-Saharan Africa. The impact, cost, and cost-effectiveness of PrEP scale-up for adolescent girls and young women (AGYW), women 25 to 34 years old, and women 35 to 49 years old were assessed, accounting for differences in population sizes and the low program retention levels reported in demonstration projects.

Results: Preexposure prophylaxis could avert substantially more infections a year among women in general population than among FSW. The greatest number of infections could be averted annually among AGYW in South Africa (24-fold that for FSW). In Zimbabwe, the greatest number of infections could be averted among women 25 to 34 years old (8-fold that for FSW); and in Kenya, similarly between AGYW and women 25 to 34 years old (3-fold that for FSW). However, the unit costs of PrEP delivery for AGYW, women 25 to 34 years old, and women 35 to 49 years old would have to reduce considerably (by 70.8%-91.0% across scenarios) for scale-up to these populations to be as cost-effective as for FSW.

Conclusions: Preexposure prophylaxis has the potential to substantially reduce new HIV infections in HIV-endemic countries in sub-Saharan Africa. This will necessitate PrEP being made widely available beyond those at highest individual risk and continued integration into a range of national services and at community level to significantly bring down the costs and improve cost-effectiveness.
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http://dx.doi.org/10.1097/OLQ.0000000000001253DOI Listing
November 2020

Predicted Impact of COVID-19 on Neglected Tropical Disease Programs and the Opportunity for Innovation.

Clin Infect Dis 2020 Sep 28. Epub 2020 Sep 28.

Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom.

Due to the COVID-19 pandemic, many key neglected tropical disease (NTD) activities have been postponed. This hindrance comes at a time when the NTDs are progressing towards their ambitious goals for 2030. Mathematical modelling on several NTDs, namely gambiense sleeping sickness, lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminthiases (STH), trachoma, and visceral leishmaniasis, shows that the impact of this disruption will vary across the diseases. Programs face a risk of resurgence, which will be fastest in high-transmission areas. Furthermore, of the mass drug administration diseases, schistosomiasis, STH, and trachoma are likely to encounter faster resurgence. The case-finding diseases (gambiense sleeping sickness and visceral leishmaniasis) are likely to have fewer cases being detected but may face an increasing underlying rate of new infections. However, once programs are able to resume, there are ways to mitigate the impact and accelerate progress towards the 2030 goals.
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http://dx.doi.org/10.1093/cid/ciaa933DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7543306PMC
September 2020

Inferring transmission trees to guide targeting of interventions against visceral leishmaniasis and post-kala-azar dermal leishmaniasis.

Proc Natl Acad Sci U S A 2020 10 24;117(41):25742-25750. Epub 2020 Sep 24.

Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London WC1H 9SH, United Kingdom.

Understanding of spatiotemporal transmission of infectious diseases has improved significantly in recent years. Advances in Bayesian inference methods for individual-level geo-located epidemiological data have enabled reconstruction of transmission trees and quantification of disease spread in space and time, while accounting for uncertainty in missing data. However, these methods have rarely been applied to endemic diseases or ones in which asymptomatic infection plays a role, for which additional estimation methods are required. Here, we develop such methods to analyze longitudinal incidence data on visceral leishmaniasis (VL) and its sequela, post-kala-azar dermal leishmaniasis (PKDL), in a highly endemic community in Bangladesh. Incorporating recent data on VL and PKDL infectiousness, we show that while VL cases drive transmission when incidence is high, the contribution of PKDL increases significantly as VL incidence declines (reaching 55% in this setting). Transmission is highly focal: 85% of mean distances from inferred infectors to their secondary VL cases were <300 m, and estimated average times from infector onset to secondary case infection were <4 mo for 88% of VL infectors, but up to 2.9 y for PKDL infectors. Estimated numbers of secondary cases per VL and PKDL case varied from 0 to 6 and were strongly correlated with the infector's duration of symptoms. Counterfactual simulations suggest that prevention of PKDL could have reduced overall VL incidence by up to 25%. These results highlight the need for prompt detection and treatment of PKDL to achieve VL elimination in the Indian subcontinent and provide quantitative estimates to guide spatiotemporally targeted interventions against VL.
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http://dx.doi.org/10.1073/pnas.2002731117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7568327PMC
October 2020

A spatio-temporal approach to short-term prediction of visceral leishmaniasis diagnoses in India.

PLoS Negl Trop Dis 2020 07 9;14(7):e0008422. Epub 2020 Jul 9.

Centre for Mathematical Modelling of Infectious Disease and Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom.

Background: The elimination programme for visceral leishmaniasis (VL) in India has seen great progress, with total cases decreasing by over 80% since 2010 and many blocks now reporting zero cases from year to year. Prompt diagnosis and treatment is critical to continue progress and avoid epidemics in the increasingly susceptible population. Short-term forecasts could be used to highlight anomalies in incidence and support health service logistics. The model which best fits the data is not necessarily most useful for prediction, yet little empirical work has been done to investigate the balance between fit and predictive performance.

Methodology/principal Findings: We developed statistical models of monthly VL case counts at block level. By evaluating a set of randomly-generated models, we found that fit and one-month-ahead prediction were strongly correlated and that rolling updates to model parameters as data accrued were not crucial for accurate prediction. The final model incorporated auto-regression over four months, spatial correlation between neighbouring blocks, and seasonality. Ninety-four percent of 10-90% prediction intervals from this model captured the observed count during a 24-month test period. Comparison of one-, three- and four-month-ahead predictions from the final model fit demonstrated that a longer time horizon yielded only a small sacrifice in predictive power for the vast majority of blocks.

Conclusions/significance: The model developed is informed by routinely-collected surveillance data as it accumulates, and predictions are sufficiently accurate and precise to be useful. Such forecasts could, for example, be used to guide stock requirements for rapid diagnostic tests and drugs. More comprehensive data on factors thought to influence geographic variation in VL burden could be incorporated, and might better explain the heterogeneity between blocks and improve uniformity of predictive performance. Integration of the approach in the management of the VL programme would be an important step to ensuring continued successful control.
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http://dx.doi.org/10.1371/journal.pntd.0008422DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7373294PMC
July 2020

When, Who, and How to Sample: Designing Practical Surveillance for 7 Neglected Tropical Diseases as We Approach Elimination.

J Infect Dis 2020 06;221(Suppl 5):S499-S502

Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom.

As neglected tropical disease programs look to consolidate the successes of moving towards elimination, we need to understand the dynamics of transmission at low prevalence to inform surveillance strategies for detecting elimination and resurgence. In this special collection, modelling insights are used to highlight drivers of local elimination, evaluate strategies for detecting resurgence, and show the importance of rational spatial sampling schemes for several neglected tropical diseases (specifically schistosomiasis, soil-transmitted helminths, lymphatic filariasis, trachoma, onchocerciasis, visceral leishmaniasis, and gambiense sleeping sickness).
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http://dx.doi.org/10.1093/infdis/jiaa198DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289548PMC
June 2020

Spatiotemporal and Socioeconomic Risk Factors for Dengue at the Province Level in Vietnam, 2013-2015: Clustering Analysis and Regression Model.

Trop Med Infect Dis 2020 May 19;5(2). Epub 2020 May 19.

Department of Global Health and Development, London School of Hygiene & Tropical Medicine, London WC1H 9SH, UK.

Dengue is a serious infectious disease threat in Vietnam, but its spatiotemporal and socioeconomic risk factors are not currently well understood at the province level across the country and on a multiannual scale. We explore spatial trends, clusters and outliers in dengue case counts at the province level from 2011-2015 and use this to extract spatiotemporal variables for regression analysis of the association between dengue case counts and selected spatiotemporal and socioeconomic variables from 2013-2015. Dengue in Vietnam follows anticipated spatial trends, with a potential two-year cycle of high-high clusters in some southern provinces. Small but significant associations are observed between dengue case counts and mobility, population density, a province's dengue rates the previous year, and average dengue rates two years previous in first and second order contiguous neighbours. Significant associations were not found between dengue case counts and housing pressure, access to electricity, clinician density, province-adjusted poverty rate, percentage of children below one vaccinated, or percentage of population in urban settings. These findings challenge assumptions about socioeconomic and spatiotemporal risk factors for dengue, and support national prevention targeting in Vietnam at the province level. They may also be of wider relevance for the study of other arboviruses, including Japanese encephalitis, Zika, and Chikungunya.
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http://dx.doi.org/10.3390/tropicalmed5020081DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7345007PMC
May 2020

Tooling-up for infectious disease transmission modelling.

Epidemics 2020 09 13;32:100395. Epub 2020 May 13.

Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK.

In this introduction to the Special Issue on methods for modelling of infectious disease epidemiology we provide a commentary and overview of the field. We suggest that the field has been through three revolutions that have focussed on specific methodological developments; disease dynamics and heterogeneity, advanced computing and inference, and complexity and application to the real-world. Infectious disease dynamics and heterogeneity dominated until the 1980s where the use of analytical models illustrated fundamental concepts such as herd immunity. The second revolution embraced the integration of data with models and the increased use of computing. From the turn of the century an emergence of novel datasets enabled improved modelling of real-world complexity. The emergence of more complex data that reflect the real-world heterogeneities in transmission resulted in the development of improved inference methods such as particle filtering. Each of these three revolutions have always kept the understanding of infectious disease spread as its motivation but have been developed through the use of new techniques, tools and the availability of data. We conclude by providing a commentary on what the next revoluition in infectious disease modelling may be.
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http://dx.doi.org/10.1016/j.epidem.2020.100395DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7219405PMC
September 2020

Trachoma Prevalence After Discontinuation of Mass Azithromycin Distribution.

J Infect Dis 2020 06;221(Suppl 5):S519-S524

Francis I Proctor Foundation, University of California, San Francisco, California, USA.

Background: As the World Health Organization seeks to eliminate trachoma by 2020, countries are beginning to control the transmission of trachomatous inflammation-follicular (TF) and discontinue mass drug administration (MDA) with oral azithromycin. We evaluated the effect of MDA discontinuation on TF1-9 prevalence at the district level.

Methods: We extracted from the available data districts with an impact survey at the end of their program cycle that initiated discontinuation of MDA (TF1-9 prevalence <5%), followed by a surveillance survey conducted to determine whether TF1-9 prevalence remained below the 5% threshold, warranting discontinuation of MDA. Two independent analyses were performed, 1 regression based and 1 simulation based, that assessed the change in TF1-9 from the impact survey to the surveillance survey.

Results: Of the 220 districts included, TF1-9 prevalence increased to >5% from impact to surveillance survey in 9% of districts. Regression analysis indicated that impact survey TF1-9 prevalence was a significant predictor of surveillance survey TF1-9 prevalence. The proportion of simulations with >5% TF1-9 prevalence in the surveillance survey was 2%, assuming the survey was conducted 4 years after MDA.

Conclusion: An increase in TF1-9 prevalence may represent disease resurgence but could also be due to measurement error. Improved diagnostic tests are crucial to elimination of TF1-9 as a public health problem.
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http://dx.doi.org/10.1093/infdis/jiz691DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289551PMC
June 2020

Is modelling complexity always needed? Insights from modelling PrEP introduction in South Africa.

J Public Health (Oxf) 2020 11;42(4):e551-e560

School of Computing, Electronics and Mathematics, Faculty of Engineering, Environment and Computing, Coventry University, Coventry, CV1 5FB, UK.

Background: Mathematical models can be powerful policymaking tools. Simple, static models are user-friendly for policymakers. More complex, dynamic models account for time-dependent changes but are complicated to understand and produce. Under which conditions are static models adequate? We compare static and dynamic model predictions of whether behavioural disinhibition could undermine the impact of HIV pre-exposure prophylaxis (PrEP) provision to female sex workers in South Africa.

Methods: A static model of HIV risk was developed and adapted into a dynamic model. Both models were used to estimate the possible reduction in condom use, following PrEP introduction, without increasing HIV risk. The results were compared over a 20-year time horizon, in two contexts: at epidemic equilibrium and during an increasing epidemic.

Results: Over time horizons of up to 5 years, the models are consistent. Over longer timeframes, the static model overstates the tolerated reduction in condom use where initial condom use is reasonably high ($\ge$50%) and/or PrEP effectiveness is low ($\le$45%), especially during an increasing epidemic.

Conclusions: Static models can provide useful deductions to guide policymaking around the introduction of a new HIV intervention over short-medium time horizons of up to 5 years. Over longer timeframes, static models may not sufficiently emphasise situations of programmatic importance, especially where underlying epidemics are still increasing.
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http://dx.doi.org/10.1093/pubmed/fdz178DOI Listing
November 2020

Impact of Changes in Detection Effort on Control of Visceral Leishmaniasis in the Indian Subcontinent.

J Infect Dis 2020 06;221(Suppl 5):S546-S553

Centre for Mathematical Modelling of Infectious Disease and Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom.

Background: Control of visceral leishmaniasis (VL) on the Indian subcontinent relies on prompt detection and treatment of symptomatic cases. Detection efforts influence the observed VL incidence and how well it reflects the underlying true incidence. As control targets are defined in terms of observed cases, there is an urgent need to understand how changes in detection delay and population coverage of improved detection affect VL control.

Methods: Using a mathematical model for transmission and control of VL, we predict the impact of reduced detection delays and/or increased population coverage of the detection programs on observed and true VL incidence and mortality.

Results: Improved case detection, either by higher coverage or reduced detection delay, causes an initial rise in observed VL incidence before a reduction. Relaxation of improved detection may lead to an apparent temporary (1 year) reduction in VL incidence, but comes with a high risk of resurging infection levels. Duration of symptoms in detected cases shows an unequivocal association with detection effort.

Conclusions: VL incidence on its own is not a reliable indicator of the performance of case detection programs. Duration of symptoms in detected cases can be used as an additional marker of the performance of case detection programs.
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http://dx.doi.org/10.1093/infdis/jiz644DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289545PMC
June 2020

Achieving Elimination as a Public Health Problem for Schistosoma mansoni and S. haematobium: When Is Community-Wide Treatment Required?

J Infect Dis 2020 06;221(Suppl 5):S525-S530

London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.

The World Health Organization (WHO) has set elimination as a public health problem (EPHP) as a goal for schistosomiasis. As the WHO treatment guidelines for schistosomiasis are currently under revision, we investigate whether school-based or community-wide treatment strategies are required for achieving the EPHP goal. In low- to moderate-transmission settings with good school enrolment, we find that school-based treatment is sufficient for achieving EPHP. However, community-wide treatment is projected to be necessary in certain high-transmission settings as well as settings with low school enrolment. Hence, the optimal treatment strategy depends on setting-specific factors such as the species present, prevalence prior to treatment, and the age profile of infection.
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http://dx.doi.org/10.1093/infdis/jiz609DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289541PMC
June 2020

Determining post-treatment surveillance criteria for predicting the elimination of Schistosoma mansoni transmission.

Parasit Vectors 2019 Sep 16;12(1):437. Epub 2019 Sep 16.

London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, St Mary's Campus, Imperial College London, Norfolk Place, London, W2 1PG, UK.

Background: The World Health Organization (WHO) has set elimination (interruption of transmission) as an end goal for schistosomiasis. However, there is currently little guidance on the monitoring and evaluation strategy required once very low prevalence levels have been reached to determine whether elimination or resurgence of the disease will occur after stopping mass drug administration (MDA) treatment.

Methods: We employ a stochastic individual-based model of Schistosoma mansoni transmission and MDA impact to determine a prevalence threshold, i.e. prevalence of infection, which can be used to determine whether elimination or resurgence will occur after stopping treatment with a given probability. Simulations are run for treatment programmes with varying probabilities of achieving elimination and for settings where adults harbour low to high burdens of infection. Prevalence is measured based on using a single Kato-Katz on two samples per individual. We calculate positive predictive values (PPV) using PPV ≥ 0.9 as a reliable measure corresponding to ≥ 90% certainty of elimination. We analyse when post-treatment surveillance should be carried out to predict elimination. We also determine the number of individuals across a single community (of 500-1000 individuals) that should be sampled to predict elimination.

Results: We find that a prevalence threshold of 1% by single Kato-Katz on two samples per individual is optimal for predicting elimination at two years (or later) after the last round of MDA using a sample size of 200 individuals across the entire community (from all ages). This holds regardless of whether the adults have a low or high burden of infection relative to school-aged children.

Conclusions: Using a prevalence threshold of 0.5% is sufficient for surveillance six months after the last round of MDA. However, as such a low prevalence can be difficult to measure in the field using Kato-Katz, we recommend using 1% two years after the last round of MDA. Higher prevalence thresholds of 2% or 5% can be used but require waiting over four years for post-treatment surveillance. Although, for treatment programmes where elimination is highly likely, these higher thresholds could be used sooner. Additionally, switching to more sensitive diagnostic techniques, will allow for a higher prevalence threshold to be employed.
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http://dx.doi.org/10.1186/s13071-019-3611-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6745786PMC
September 2019

Genomic analysis of respiratory syncytial virus infections in households and utility in inferring who infects the infant.

Sci Rep 2019 07 11;9(1):10076. Epub 2019 Jul 11.

Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Epidemiology and Demography Department, Kilifi, Kenya.

Infants (under 1-year-old) are at most risk of life threatening respiratory syncytial virus (RSV) disease. RSV epidemiological data alone has been insufficient in defining who acquires infection from whom (WAIFW) within households. We investigated RSV genomic variation within and between infected individuals and assessed its potential utility in tracking transmission in households. Over an entire single RSV season in coastal Kenya, nasal swabs were collected from members of 20 households every 3-4 days regardless of symptom status and screened for RSV nucleic acid. Next generation sequencing was used to generate >90% RSV full-length genomes for 51.1% of positive samples (191/374). Single nucleotide polymorphisms (SNPs) observed during household infection outbreaks ranged from 0-21 (median: 3) while SNPs observed during single-host infection episodes ranged from 0-17 (median: 1). Using the viral genomic data alone there was insufficient resolution to fully reconstruct within-household transmission chains. For households with clear index cases, the most likely source of infant infection was via a toddler (aged 1 to <3 years-old) or school-aged (aged 6 to <12 years-old) co-occupant. However, for best resolution of WAIFW within households, we suggest an integrated analysis of RSV genomic and epidemiological data.
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http://dx.doi.org/10.1038/s41598-019-46509-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6624209PMC
July 2019

Modeling household dynamics on Respiratory Syncytial Virus (RSV).

PLoS One 2019 9;14(7):e0219323. Epub 2019 Jul 9.

Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.

Respiratory Syncytial Virus (RSV) is the most common cause of respiratory tract infection in infants and children and shows increasing trend among elderly people worldwide. In many developing country settings, population and household structures have gone through some significant changes in the past decades, namely fewer births, more elderly population, and smaller household size but more RSV high-risk individuals. These dynamics have been captured in a mathematical model with RSV transmission dynamics to predict the disease burden on the detailed population for future targeted interventions. The population and disease dynamics model was constructed and tested against the hospitalization data for Acute Lower Respiratory Tract Infection due to RSV in rural Thai settings between 2005 and 2011. The proportion of extended families is predicted to increase by about 10% from 2005 to 2020, especially for those with elderly population, while the classic nuclear family type (with adults and children) will decline by about 10%. For RSV, infections from extended family type (approximately 60% of all household types) have majorly contributed to the force of infection (FOI). While the model predicted the increase of FOI from the extended family by 15% from 2005 to 2020, the FOI contributed by other household types would be either stable or decrease in the same time period. RSV incidence rate is predominantly high among babies (92.2%) and has been predicted to decrease slightly over time (from 940 to 864 cases per 100,000 population by 2020), while the incidence rates among children and elderly people may remain steadily low over the same period. However, the estimated incidence rates among elderly people were twice than those in children. The model predicts that approximately 60% of FOI for RSV will come from members of the extended family type. The incidence rate of RSV among children and elderly in extended families was about 20 times lower than that in infants and the trend is steady. Targeted intervention strategies, such as health education in some specific groups and targeted vaccination, may be considered, with the focus on extended family type. Target interventions on babies can lessen the transmission to children and elderly especially when transmission within households of extended family type is high.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0219323PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6615606PMC
March 2020

Assessing the cost-effectiveness of HPV vaccination strategies for adolescent girls and boys in the UK.

BMC Infect Dis 2019 Jun 24;19(1):552. Epub 2019 Jun 24.

Zeeman Institute: SBIDER, Warwick Mathematics Institute and School of Life Sciences, The University of Warwick, Coventry, CV4 8UW, UK.

Background: Human papillomavirus (HPV) is the most widespread sexually transmitted infection worldwide. It causes several health consequences, in particular accounting for the majority of cervical cancer cases in women. In the United Kingdom, a vaccination campaign targeting 12-year-old girls started in 2008; this campaign has been successful, with high uptake and reduced HPV prevalence observed in vaccinated cohorts. Recently, attention has focused on vaccinating both sexes, due to HPV-related diseases in males (particularly for high-risk men who have sex with men) and an equity argument over equalising levels of protection.

Methods: We constructed an epidemiological model for HPV transmission in the UK, accounting for nine of the most common HPV strains. We complemented this with an economic model to determine the likely health outcomes (healthcare costs and quality-adjusted life years) for individuals from the epidemiological model. We then tested vaccination with the three HPV vaccines currently available, vaccinating either girls alone or both sexes. For each strategy we calculated the threshold price per vaccine dose, i.e. the maximum amount paid for the added health benefits of vaccination to be worth the cost of each vaccine dose. We calculated results at 3.5% discounting, and also 1.5%, to consider the long-term health effects of HPV infection.

Results: At 3.5% discounting, continuing to vaccinate girls remains highly cost-effective compared to halting vaccination, with threshold dose prices of £56-£108. Vaccination of girls and boys is less cost-effective (£25-£53). Compared to vaccinating girls only, adding boys to the programme is not cost-effective, with negative threshold prices (-£6 to -£3) due to the costs of administration. All threshold prices increase when using 1.5% discounting, and adding boys becomes cost-effective (£36-£47). These results are contingent on the UK's high vaccine uptake; for lower uptake rates, adding boys (at the same uptake rate) becomes more cost effective.

Conclusions: Vaccinating girls is extremely cost-effective compared with no vaccination, vaccinating both sexes is less so. Adding boys to an already successful girls-only programme has a low cost-effectiveness, as males have high protection through herd immunity. If future health effects are weighted more heavily, threshold prices increase and vaccination becomes cost-effective.
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http://dx.doi.org/10.1186/s12879-019-4108-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6591963PMC
June 2019

A Population Dynamic Model to Assess the Diabetes Screening and Reporting Programs and Project the Burden of Undiagnosed Diabetes in Thailand.

Int J Environ Res Public Health 2019 06 21;16(12). Epub 2019 Jun 21.

Centre for Mathematical Modelling of Infectious Disease & Department of Global Health and Development, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK.

Diabetes mellitus (DM) is rising worldwide, exacerbated by aging populations. We estimated and predicted the diabetes burden and mortality due to undiagnosed diabetes together with screening program efficacy and reporting completeness in Thailand, in the context of demographic changes. An age and sex structured dynamic model including demographic and diagnostic processes was constructed. The model was validated using a Bayesian Markov Chain Monte Carlo (MCMC) approach. The prevalence of DM was predicted to increase from 6.5% (95% credible interval: 6.3-6.7%) in 2015 to 10.69% (10.4-11.0%) in 2035, with the largest increase (72%) among 60 years or older. Out of the total DM cases in 2015, the percentage of undiagnosed DM cases was 18.2% (17.4-18.9%), with males higher than females (-value < 0.01). The highest group with undiagnosed DM was those aged less than 39 years old, 74.2% (73.7-74.7%). The mortality of undiagnosed DM was ten-fold greater than the mortality of those with diagnosed DM. The estimated coverage of diabetes positive screening programs was ten-fold greater for elderly compared to young. The positive screening rate among females was estimated to be significantly higher than those in males. Of the diagnoses, 87.4% (87.0-87.8%) were reported. Targeting screening programs and good reporting systems will be essential to reduce the burden of disease.
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http://dx.doi.org/10.3390/ijerph16122207DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6617291PMC
June 2019

Modelling population dynamics and seasonal movement to assess and predict the burden of melioidosis.

PLoS Negl Trop Dis 2019 05 9;13(5):e0007380. Epub 2019 May 9.

Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.

Background: Melioidosis is an infectious disease that is transmitted mainly through contact with contaminated soil or water, and exhibits marked seasonality in most settings, including Southeast Asia. In this study, we used mathematical modelling to examine the impacts of such demographic changes on melioidosis incidence, and to predict the disease burden in a developing country such as Thailand.

Methodology/principal Findings: A melioidosis infection model was constructed which included demographic data, diabetes mellitus (DM) prevalence, and melioidosis disease processes. The model was fitted to reported melioidosis incidence in Thailand by age, sex, and geographical area, between 2008 and 2015, using a Bayesian Markov Chain Monte Carlo (MCMC) approach. The model was then used to predict the disease burden and future trends of melioidosis incidence in Thailand. Our model predicted two-fold higher incidence rates of melioidosis compared with national surveillance data from 2015. The estimated incidence rates among males were two-fold greater than those in females. Furthermore, the melioidosis incidence rates in the Northeast region population, and among the transient population, were more than double compared to the non-Northeast region population. The highest incidence rates occurred in males aged 45-59 years old for all regions. The average incidence rate of melioidosis between 2005 and 2035 was predicted to be 11.42 to 12.78 per 100,000 population per year, with a slightly increasing trend. Overall, it was estimated that about half of all cases of melioidosis were symptomatic. In addition, the model suggested a greater susceptibility to melioidosis in diabetic compared with non-diabetic individuals.

Conclusions/significance: The increasing trend of melioidosis incidence rates was significantly higher among working-age Northeast and transient populations, males aged ≥45 years old, and diabetic individuals. Targeted intervention strategies, such as health education and awareness raising initiatives, should be implemented on high-risk groups, such as those living in the Northeast region, and the seasonally transient population.
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http://dx.doi.org/10.1371/journal.pntd.0007380DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6529009PMC
May 2019

Model-based estimates of transmission of respiratory syncytial virus within households.

Epidemics 2019 06 15;27:1-11. Epub 2018 Dec 15.

Centre for Mathematical Modelling of Infectious Disease and Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, WC1H 9SH, UK.

Introduction: Respiratory syncytial virus (RSV) causes a significant respiratory disease burden in the under 5 population. The transmission pathway to young children is not fully quantified in low-income settings, and this information is required to design interventions.

Methods: We used an individual level transmission model to infer transmission parameters using data collected from 493 individuals distributed across 47 households over a period of 6 months spanning the 2009/2010 RSV season. A total of 208 episodes of RSV were observed from 179 individuals. We model competing transmission risk from within household exposure and community exposure while making a distinction between RSV groups A and B.

Results: We find that 32-53% of all RSV transmissions are between members of the same household; the rate of pair-wise transmission is 58% (95% CrI: 30-74%) lower in larger households (≥8 occupants) than smaller households; symptomatic individuals are 2-7 times more infectious than asymptomatic individuals i.e. 2.48 (95% CrI: 1.22-5.57) among symptomatic individuals with low viral load and 6.7(95% CrI: 2.56-16) among symptomatic individuals with high viral load; previous infection reduces susceptibility to re-infection within the same epidemic by 47% (95% CrI: 17%-68%) for homologous RSV group and 39% (95%CrI: -8%-69%) for heterologous group; RSV B is more frequently introduced into the household, and RSV A is more rapidly transmitted once in the household.

Discussion: Our analysis presents the first transmission modelling of cohort data for RSV and we find that it is important to consider the household social structuring and household size when modelling transmission. The increased infectiousness of symptomatic individuals implies that a vaccine against RSV related disease would also have an impact on infection transmission. Together, the weak cross immunity between RSV groups and the possibility of different transmission niches could form part of the explanation for the group co-existence.
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http://dx.doi.org/10.1016/j.epidem.2018.12.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6543068PMC
June 2019

An Intensive, Active Surveillance Reveals Continuous Invasion and High Diversity of Rhinovirus in Households.

J Infect Dis 2019 03;219(7):1049-1057

Epidemiology and Demography Department, Kenya Medical Research Institute - Wellcome Trust Research Programme, Kilifi.

We report on infection patterns in 5 households (78 participants) delineating the natural history of human rhinovirus (HRV). Nasopharyngeal collections were obtained every 3-4 days irrespective of symptoms, over a 6-month period, with molecular screening for HRV and typing by sequencing VP4/VP2 junction. Overall, 311/3468 (8.9%) collections were HRV positive: 256 were classified into 3 species: 104 (40.6%) HRV-A; 14 (5.5%) HRV-B, and 138 (53.9%) HRV-C. Twenty-six known HRV types (13 HRV-A, 3 HRV-B, and 10 HRV-C) were identified (A75, C1, and C35 being most frequent). We observed continuous invasion and temporal clustering of HRV types in households (range 5-13 over 6 months). Intrahousehold transmission was independent of clinical status but influenced by age. Most (89.0%) of HRV infection episodes were limited to <14 days. Individual repeat infections were frequent (range 1-7 over 6 months), decreasing with age, and almost invariably heterotypic, indicative of lasting type-specific immunity and low cross-type protection.
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http://dx.doi.org/10.1093/infdis/jiy621DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6420174PMC
March 2019

Age trends in asymptomatic and symptomatic Leishmania donovani infection in the Indian subcontinent: A review and analysis of data from diagnostic and epidemiological studies.

PLoS Negl Trop Dis 2018 12 6;12(12):e0006803. Epub 2018 Dec 6.

Zeeman Institute, University of Warwick, Coventry, United Kingdom.

Background: Age patterns in asymptomatic and symptomatic infection with Leishmania donovani, the causative agent of visceral leishmaniasis (VL) in the Indian subcontinent (ISC), are currently poorly understood. Age-stratified serology and infection incidence have been used to assess transmission levels of other diseases, which suggests that they may also be of use for monitoring and targeting control programmes to achieve elimination of VL and should be included in VL transmission dynamic models. We therefore analysed available age-stratified data on both disease incidence and prevalence of immune markers with the aim of collating the currently available data, estimating rates of infection, and informing modelling and future data collection.

Methodology/principal Findings: A systematic literature search yielded 13 infection prevalence and 7 VL incidence studies meeting the inclusion criteria. Statistical tests were performed to identify trends by age, and according to diagnostic cut-off. Simple reversible catalytic models with age-independent and age-dependent infection rates were fitted to the prevalence data to estimate infection and reversion rates, and to test different hypotheses about the origin of variation in these rates. Most of the studies showed an increase in infection prevalence with age: from ≲10% seroprevalence (<20% Leishmanin skin test (LST) positivity) for 0-10-year-olds to >10% seroprevalence (>20% LST-positivity) for 30-40-year-olds, but overall prevalence varied considerably between studies. VL incidence was lower amongst 0-5-year-olds than older age groups in most studies; most showing a peak in incidence between ages 5 and 20. The age-independent catalytic model provided the best overall fit to the infection prevalence data, but the estimated rates for the less parsimonious age-dependent model were much closer to estimates from longitudinal studies, suggesting that infection rates may increase with age.

Conclusions/significance: Age patterns in asymptomatic infection prevalence and VL incidence in the ISC vary considerably with geographical location and time period. The increase in infection prevalence with age and peaked age-VL-incidence distribution may be due to lower exposure to infectious sandfly bites in young children, but also suggest that acquired immunity to the parasite increases with age. However, poor standardisation of serological tests makes it difficult to compare data from different studies and draw firm conclusions about drivers of variation in observed age patterns.
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http://dx.doi.org/10.1371/journal.pntd.0006803DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6283524PMC
December 2018

The role of case proximity in transmission of visceral leishmaniasis in a highly endemic village in Bangladesh.

PLoS Negl Trop Dis 2018 10 8;12(10):e0006453. Epub 2018 Oct 8.

Zeeman Institute, University of Warwick, Coventry, UK.

Background: Visceral leishmaniasis (VL) is characterised by a high degree of spatial clustering at all scales, and this feature remains even with successful control measures. VL is targeted for elimination as a public health problem in the Indian subcontinent by 2020, and incidence has been falling rapidly since 2011. Current control is based on early diagnosis and treatment of clinical cases, and blanket indoor residual spraying of insecticide (IRS) in endemic villages to kill the sandfly vectors. Spatially targeting active case detection and/or IRS to higher risk areas would greatly reduce costs of control, but its effectiveness as a control strategy is unknown. The effectiveness depends on two key unknowns: how quickly transmission risk decreases with distance from a VL case and how much asymptomatically infected individuals contribute to transmission.

Methodology/principal Findings: To estimate these key parameters, a spatiotemporal transmission model for VL was developed and fitted to geo-located epidemiological data on 2494 individuals from a highly endemic village in Mymensingh, Bangladesh. A Bayesian inference framework that could account for the unknown infection times of the VL cases, and missing symptom onset and recovery times, was developed to perform the parameter estimation. The parameter estimates obtained suggest that, in a highly endemic setting, VL risk decreases relatively quickly with distance from a case-halving within 90m-and that VL cases contribute significantly more to transmission than asymptomatic individuals.

Conclusions/significance: These results suggest that spatially-targeted interventions may be effective for limiting transmission. However, the extent to which spatial transmission patterns and the asymptomatic contribution vary with VL endemicity and over time is uncertain. In any event, interventions would need to be performed promptly and in a large radius (≥300m) around a new case to reduce transmission risk.
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http://dx.doi.org/10.1371/journal.pntd.0006453DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6175508PMC
October 2018

The design of schistosomiasis monitoring and evaluation programmes: The importance of collecting adult data to inform treatment strategies for Schistosoma mansoni.

PLoS Negl Trop Dis 2018 10 8;12(10):e0006717. Epub 2018 Oct 8.

London Centre for Neglected Tropical Disease Research and Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, St Mary's Campus, Imperial College London, London, United Kingdom.

Monitoring and evaluation (M&E) programmes are used to collect data which are required to assess the impact of current interventions on their progress towards achieving the World Health Organization (WHO) goals of morbidity control and elimination as a public health problem for schistosomiasis. Prevalence and intensity of infection data are typically collected from school-aged children (SAC) as they are relatively easy to sample and are thought to be most likely to be infected by schistosome parasites. However, adults are also likely to be infected. We use three different age-intensity profiles of infection for Schistosoma mansoni with low, moderate and high burdens of infection in adults to investigate how the age distribution of infection impacts the mathematical model generated recommendations of the preventive chemotherapy coverage levels required to achieve the WHO goals. We find that for moderate prevalence regions, regardless of the burden of infection in adults, treating SAC only may achieve the WHO goals. However, for high prevalence regions with a high burden of infection in adults, adult treatment is required to meet the WHO goals. Hence, we show that the optimal treatment strategy for a defined region requires consideration of the burden of infection in adults as it cannot be based solely on the prevalence of infection in SAC. Although past epidemiological data have informed mathematical models for the transmission and control of schistosome infections, more accurate and detailed data are required from M&E programmes to accurately determine the optimal treatment strategy for a defined region. We highlight the importance of collecting prevalence and intensity of infection data from a broader age-range, specifically the inclusion of adult data at baseline (prior to treatment) and throughout the treatment programme if possible, rather than SAC only, to accurately determine the treatment strategy for a defined region. Furthermore, we discuss additional epidemiological data, such as individual longitudinal adherence to treatment, that should ideally be collected in M&E programmes.
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http://dx.doi.org/10.1371/journal.pntd.0006717DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6175503PMC
October 2018