Continental-Scale, Data-Driven Predictive Assessment of Eliminating the Vector-Borne Disease, Lymphatic Filariasis, in Sub-Saharan Africa by 2020

Michael, E.; Singh, Bhavna; Mayala, Benjamin K.; Smith, Morgan E.; Hampton, Scott; Nabrzyski, Jarosław

doi:10.1016/j.jvsv.2017.12.003

Cited by 8 publications

(13 citation statements)

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“…The data sources used for calibrating the LF model were collected from Léogâne commune, Haiti [28–31]. The epidemiological data inputs encompassed information on baseline community-level mf prevalence (15.5%), the annual biting rate (ABR) estimated inversely by model fitting to mf prevalence data [39], and details regarding the dominant mosquito genus ( Culex quinquefasciatus ). Published details of the MDA interventions, including the relevant drug regimen, carried out in this setting during 2000-2008 were also assembled and used as required [20,28–31].…”

Section: Methodsmentioning

confidence: 99%

Economic performance and cost-effectiveness of using a DEC-salt social enterprise for eliminating the major neglected tropical disease, lymphatic filariasis

Sharma

Smith

Reimer

et al. 2018

Preprint

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Background Salt fortified with the drug, diethylcarbamazine (DEC), and introduced into a competitive market has the potential to overcome the obstacles associated with tablet-based Lymphatic Filariasis (LF) elimination programs. Questions remain, however, regarding the economic viability, production capacity, and effectiveness of this strategy as a sustainable means to bring about LF elimination in resource poor settings. Methodology and Principal Findings We evaluated the performance and effectiveness of a novel social enterprise-based approach developed and tested in Léogâne, Haiti, as a strategy to sustainably and cost-efficiently distribute DEC-medicated salt into a competitive market at quantities sufficient to bring about the elimination of LF. We undertook a cost-revenue analysis to evaluate the production capability and financial feasibility of the developed DEC salt social enterprise, and a modeling study centered on applying a dynamic mathematical model localized to reflect local LF transmission dynamics to evaluate the cost-effectiveness of using this intervention versus standard annual Mass Drug Administration (MDA) for eliminating LF in Léogâne. We show that the salt enterprise because of its mixed product business strategy may have already reached the production capacity for delivering sufficient quantities of edible DEC-medicated salt to bring about LF transmission in the Léogâne study setting. Due to increasing revenues obtained from the sale of DEC salt over time, expansion of its delivery in the population, and greater cumulative impact on the survival of worms, this strategy could also represent a significantly more cost-effective option than annual DEC tablet-based MDA for accomplishing LF elimination. Significance A social enterprise approach can offer an innovative market-based strategy by which edible salt fortified with DEC could be distributed to communities both on a financially sustainable basis and at sufficient quantity to eliminate LF. Deployment of similarly fashioned intervention strategies would improve current efforts to successfully accomplish the goal of LF elimination, particularly in difficult-to-control settings.

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Section: Methodsmentioning

confidence: 99%

Economic performance and cost-effectiveness of using a DEC-salt social enterprise for eliminating the major neglected tropical disease, lymphatic filariasis

Sharma

Smith

Reimer

et al. 2018

Preprint

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“…Estimating site-specific ABRs. Previous studies have shown that the key environmental driver that governs pattern-process relationships in the case of vector-borne macroparasitic infections, and hence that primarily constrains a model's parameter space so that the effects of local transmission conditions are captured, is the vector biting rate obtaining in a community 4,7,25,30 . However, in this study, the baseline data for each study village included information on this driving variable only at the higher aggregate focus level as described above.…”

Section: Datamentioning

confidence: 99%

“…To perform this exercise, each of the randomly sampled parameter vectors was used to obtain plausible ABR values by running the model under a standard root finding algorithm for which the model-generated overall mf prevalence matched the observed baseline community mf prevalence within a tolerance limit of 0.001 or lower. This root-finding algorithm was implemented in Matlab using its built-in fzero function 4 . The same procedure was also used to estimate the missing ABR data for the Bwindi sites.…”

Section: Datamentioning

confidence: 99%

“…posed by spatial variability and complexity for efforts to understand and predict the dynamics of natural systems across landscapes of interest 4,[20][21][22][23][24] . This topic is also receiving increased attention among the major agencies and actors in parasitic disease control given the emergent concerns regarding the consequences of variations in initial endemicity levels and the impacts of persisting spatial hotspots of transmission for current efforts to accomplish area-wide disease elimination [25][26][27] .…”

mentioning

confidence: 99%

“…producing/accepting high false positive or Type I errors 14 ) for guiding effective parasite control. While these studies have suggested the need for a heterogeneity-based paradigm for both modelling and managing a macroparasitic disease 4,25,30 , it is not clear whether the impact of spatial complexity is as significant and applies also to less locally-driven vector-borne diseases exhibiting more homogeneous transmission patterns within an endemic zone. According to this perspective, it is possible that a homogeneous spatial domain may exist within which one may assume the operation of an aggregated, stable, and stationary or constant relationship between the processes and patterns of transmission 21,22 , which would obviate the need to further address the effects of any finer scale spatial heterogeneities.…”

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confidence: 99%

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

Michael

Smith

Singh

et al. 2020

Sci Rep

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edson Byamukama 3 , peace Habomugisha 3 , thomson Lakwo 4 , edridah tukahebwa 4 & frank o. Richards 2 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 heterogeneitybased 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. In recent years, there has been growing appreciation of the role that mathematical models can play in guiding the control or eradication of the major preventable helminthic diseases, ranging from soil-transmitted helminthiases to schistosomiasis, lymphatic filariasis (LF), and onchocerciasis 1-11. This recognition has been catalysed by the expectation that quantitative mathematical models can provide a robust scientific basis for predicting the course of infection resulting from perturbations induced by interventions 12. A second major reason is the implicit belief that making such ecological predictions is possible, despite the complex, nonlinear, and open nature of the parasitic systems being studied and the approximations necessary to translate understanding of these systems into computer programs 4,13-15. Despite these constraints, helminth transmission models are created and used today in the belief not only that they offer the best available tools for providing dependable predictions of the future states of such systems, but also that they will continue to evolve towards more realistic representations of parasitic systems as knowledge of transmission processes and structures improves over time 16,17. Apart from the above challenges, which in essence question the intrinsic predictability of any complex ecological system 15,18,19 , a growing strand ...

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Evaluating the Evidence for Lymphatic Filariasis Elimination

Davis

Reimer

Pellis

et al. 2019

Trends in Parasitology

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In the global drive for elimination of lymphatic filariasis (LF), 15 countries have achieved validation of elimination as a public health problem (EPHP). Recent empirical evidence has demonstrated that EPHP does not always lead to elimination of transmission (EOT). Here we show how the probability of elimination explicitly depends on key biological parameters, many of which have been poorly characterized, leading to a poor evidence base for the elimination threshold. As more countries progress towards EPHP it is essential that this process is well-informed, as prematurely halting treatment and surveillance programs could pose a serious threat to global progress. We highlight that refinement of the weak empirical evidence base is vital to understand drivers of elimination and inform long-term policy.

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Continental-Scale, Data-Driven Predictive Assessment of Eliminating the Vector-Borne Disease, Lymphatic Filariasis, in Sub-Saharan Africa by 2020

Cited by 8 publications

References 56 publications

Economic performance and cost-effectiveness of using a DEC-salt social enterprise for eliminating the major neglected tropical disease, lymphatic filariasis

Economic performance and cost-effectiveness of using a DEC-salt social enterprise for eliminating the major neglected tropical disease, lymphatic filariasis

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

Evaluating the Evidence for Lymphatic Filariasis Elimination

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