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http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/301| Stochastic challenges to interrupting helminth transmission | |
| Marleen Werkman James E Truscott Roy M Anderson Robert J Hardwick | |
| Novel Coronavirus | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| 10.1101/2019.12.17.19013490 | |
| Predicting the effect of different programmes designed to control both the morbidity induced by helminth infections and parasite transmission is greatly facilitated by the use of mathematical models of transmission and control impact. In such models, it is essential to account for as many sources of uncertainty -- natural, or otherwise -- to ensure robustness in prediction and to accurately depict variation around an expected outcome. In this paper, we investigate how well the standard deterministic models match the predictions made using individual-based stochastic simulations. We also explore how well concepts which derive from deterministic models, such as ‘breakpoints’ in transmission, apply in the stochastic world. Employing an individual based stochastic model framework we also investigate how transmission and control are affected by the migration of infected people into a defined community. To give our study focus we consider the control of soil-transmitted helminths (STH) by mass drug administration (MDA), though our methodology is readily applicable to the other helminth species such as the schistosome parasites and the filarial worms. We show it is possible to define a ‘stochastic breakpoint’ where much noise surrounds the expected deterministic breakpoint. We also discuss the concept of the ‘interruption of transmission’ independent of the ‘breakpoint’ concept where analyses of model behaviour illustrate the current limitations of deterministic models to account for the ‘fade-out’ or transmission extinction behaviour in simulations. The analyses based on migration confirm a relationship between the infected human migration rate per unit of time and the death rate of infective stages that are released into the free-living environment (eggs or larvae depending on the STH species) that create the reservoir of infection which in turn determines the likelihood that control activities aim at chemotherapeutic treatment of the human host will eliminate transmission. The development of a new stochastic simulation code for STH in the form of a publicly-available open-source python package which includes features to incorporate many population stratifications, different control interventions including mass drug administration (with defined frequency, coverage levels and compliance patterns) and inter-village human migration is also described. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement RJH, MW, JET and RMA gratefully thank the Bill and Melinda Gates Foundation for research grant support via the DeWorm3 (OPP1129535) award to the Natural History Museum in London (href{http://www.gatesfoundation.org/}{http://www.gatesfoundation.org/}). The authors would also like to thank Emily McNaughton for project management and helpful comments on the manuscript. The views, opinions, assumptions or any other information set out in this article are solely those of the authors. All authors acknowledge joint Centre funding from the UK Medical Research Council and Department for International Development (MR/R015600/1). ### Author Declarations All relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript. Yes All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes NA | |
| Cold Spring Harbor Laboratory Press | |
| 2019 | |
| Preimpreso | |
| https://www.medrxiv.org/content/10.1101/2019.12.17.19013490v1 | |
| Inglés | |
| VIRUS RESPIRATORIOS | |
| Aparece en las colecciones: | Artículos científicos |
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| Fichero | Tamaño | Formato | |
|---|---|---|---|
| Stochastic challenges.pdf | 6.62 MB | Adobe PDF | Visualizar/Abrir |