Dataset Information

Data-driven modelling and spatial complexity supports heterogeneity-based integrative management for eliminating Simulium neavei-transmitted river blindness.

ABSTRACT: Concern is emerging regarding the challenges posed by spatial complexity for modelling and managing the area-wide elimination of parasitic infections. While this has led to calls for applying heterogeneity-based approaches for addressing this complexity, questions related to spatial scale, the discovery of locally-relevant models, and its interaction with options for interrupting parasite transmission remain to be resolved. We used a data-driven modelling framework applied to infection data gathered from different monitoring sites to investigate these questions in the context of understanding the transmission dynamics and efforts to eliminate Simulium neavei- transmitted onchocerciasis, a macroparasitic disease that causes river blindness in Western Uganda and other regions of Africa. We demonstrate that our Bayesian-based data-model assimilation technique is able to discover onchocerciasis models that reflect local transmission conditions reliably. Key management variables such as infection breakpoints and required durations of drug interventions for achieving elimination varied spatially due to site-specific parameter constraining; however, this spatial effect was found to operate at the larger focus level, although intriguingly including vector control overcame this variability. These results show that data-driven modelling based on spatial datasets and model-data fusing methodologies will be critical to identifying both the scale-dependent models and heterogeneity-based options required for supporting the successful elimination of S. neavei-borne onchocerciasis.

SUBMITTER: Michael E

PROVIDER: S-EPMC7060237 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Data-driven modelling and spatial complexity supports heterogeneity-based integrative management for eliminating Simulium neavei-transmitted river blindness.

Michael Edwin E Smith Morgan E ME Singh Brajendra K BK Katabarwa Moses N MN Byamukama Edson E Habomugisha Peace P Lakwo Thomson T Tukahebwa Edridah E Richards Frank O FO

Scientific reports 20200306 1

Concern is emerging regarding the challenges posed by spatial complexity for modelling and managing the area-wide elimination of parasitic infections. While this has led to calls for applying heterogeneity-based approaches for addressing this complexity, questions related to spatial scale, the discovery of locally-relevant models, and its interaction with options for interrupting parasite transmission remain to be resolved. We used a data-driven modelling framework applied to infection data gath ...[more]

PMID: 32144362

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Project description:The onchocerciasis transmission models EPIONCHO and ONCHOSIM have been independently developed and used to explore the feasibility of eliminating onchocerciasis from Africa with mass (annual or biannual) distribution of ivermectin within the timeframes proposed by the World Health Organization (WHO) and endorsed by the 2012 London Declaration on Neglected Tropical Diseases (i.e. by 2020/2025). Based on the findings of our previous model comparison, we implemented technical refinements and tested the projections of EPIONCHO and ONCHOSIM against long-term epidemiological data from two West African transmission foci in Mali and Senegal where the observed prevalence of infection was brought to zero circa 2007-2009 after 15-17 years of mass ivermectin treatment. We simulated these interventions using programmatic information on the frequency and coverage of mass treatments and trained the model projections using longitudinal parasitological data from 27 communities, evaluating the projected outcome of elimination (local parasite extinction) or resurgence. We found that EPIONCHO and ONCHOSIM captured adequately the epidemiological trends during mass treatment but that resurgence, while never predicted by ONCHOSIM, was predicted by EPIONCHO in some communities with the highest (inferred) vector biting rates and associated pre-intervention endemicities. Resurgence can be extremely protracted such that low (microfilarial) prevalence between 1% and 5% can be maintained for 3-5 years before manifesting more prominently. We highlight that post-treatment and post-elimination surveillance protocols must be implemented for long enough and with high enough sensitivity to detect possible residual latent infections potentially indicative of resurgence. We also discuss uncertainty and differences between EPIONCHO and ONCHOSIM projections, the potential importance of vector control in high-transmission settings as a complementary intervention strategy, and the short remaining timeline for African countries to be ready to stop treatment safely and begin surveillance in order to meet the impending 2020/2025 elimination targets.

Project description:BackgroundThe African Programme for Onchocerciasis Control (APOC) has refocused its goals on the elimination of infection where possible, seemingly achievable by 15-17 years of annual mass distribution of ivermectin in some African foci. Previously, APOC had focused on the elimination of onchocerciasis as a public health problem. Timeframes have been set by the World Health Organization, the London Declaration on Neglected Tropical Diseases and the World Bank to achieve these goals by 2020-2025.MethodsA novel mathematical model of the dynamics of onchocercal disease is presented which links documented associations between Onchocerca volvulus infection and the prevalence and incidence of morbidity and mortality to model outputs from our host age- and sex-structured onchocerciasis transmission framework (EpiOncho). The model is calibrated for African savannah settings, and used to assess the impact of long-term annual mass administration of ivermectin on infection and ocular and skin disease and to explore how this depends on epidemiological and programmatic variables.ResultsCurrent onchocerciasis disease projections, which do not account for excess mortality of sighted individuals with heavy microfilarial loads, underestimate disease burden. Long-term annual ivermectin treatment is highly effective at reducing both the morbidity and mortality associated with onchocerciasis, and this result is not greatly influenced by treatment coverage and compliance. By contrast, impact on microfilarial prevalence and intensity is highly dependent on baseline endemicity, treatment coverage and systematic non-compliance.ConclusionsThe goals of eliminating morbidity and infection with ivermectin alone are distinctly influenced by epidemiological and programmatic factors. Whilst the former goal is most certainly achievable, reaching the latter will strongly depend on initial endemicity (the higher the endemicity, the greater the magnitude of inter-treatment transmission), advising caution when generalising the applicability of successful elimination outcomes to other areas. The proportion of systematic non-compliers will become far more influential in terms of overall success in achieving elimination goals.

Dataset Information

Data-driven modelling and spatial complexity supports heterogeneity-based integrative management for eliminating Simulium neavei-transmitted river blindness.

Publications

Data-driven modelling and spatial complexity supports heterogeneity-based integrative management for eliminating Simulium neavei-transmitted river blindness.

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