title: An ecological model for quantitative risk assessment for schistosomiasis: the case of a patchy environment in the coastal tropical area of northeastern Brazil.
abstract: We developed a stochastic model for quantitative risk assessment for the Schistosoma mansoni (SM) parasite, which causes an endemic disease of public concern. The model provides answers in a useful format for public health decisions, uses data and expert opinion, and can be applied to any landscape where the snail Biomphalaria glabrata is the main intermediate host (South and Central America, the Caribbean, and Africa). It incorporates several realistic and case-specific features: stage-structured parasite populations, periodic praziquantel (PZQ) drug treatment for humans, density dependence, extreme events (prolonged rainfall), site-specific sanitation quality, environmental stochasticity, monthly rainfall variation, uncertainty in parameters, and spatial dynamics. We parameterize the model through a real-world application in the district of Porto de Galinhas (PG), one of the main touristic destinations in Brazil, where previous studies identified four parasite populations within the metapopulation. The results provide a good approximation of the dynamics of the system and are in agreement with our field observations, i.e., the lack of basic infrastructure (sanitation level and health programs) makes PG a suitable habitat for the persistence and growth of a parasite metapopulation. We quantify the risk of SM metapopulation explosion and quasi-extinction and the time to metapopulation explosion and quasi-extinction. We evaluate the sensitivity of the results under varying scenarios of future periodic PZQ treatment (based on the Brazilian Ministry of Health's plan) and sanitation quality. We conclude that the plan might be useful to slow SM metapopulation growth but not to control it. Additional investments in better sanitation are necessary.
authors.affiliation: Department of Production Engineering, Centre for Risk Analysis and Environmental Modeling (CEERMA), Federal University of Pernambuco, Recife, Pernambuco, Brazil.
authors.forename: Heitor de Oliveira
authors.initials: Hde O
authors.lastname: Duarte
authors.forename: Enrique Lopez
authors.initials: EL
authors.lastname: Droguett
authors.forename: Márcio das Chagas
authors.initials: Md
authors.lastname: Moura
authors.forename: Elainne Christine de Souza
authors.initials: EC
authors.lastname: Gomes
authors.forename: Constança
authors.initials: C
authors.lastname: Barbosa
authors.forename: Verônica
authors.initials: V
authors.lastname: Barbosa
authors.forename: Moacyr
authors.initials: M
authors.lastname: Araújo
mesh_terms: D001938:Brazil / Q000453:epidemiology; D006801:Humans; D008962:Models, Theoretical; D018570:Risk Assessment; D012552:Schistosomiasis / Q000453:epidemiology*; D014329:Tropical Climate
keywords: Ecological model; endemic disease; microbial quantitative risk assessment