Community-Directed Vector Control to Accelerate Onchocerciasis Elimination.

Onchocerciasis, or river blindness, has historically been one of the most important causes of blindness worldwide, and a major cause of socio-economic disruption, particularly in sub-Saharan Africa. Its importance as a cause of morbidity and an impediment to economic development in some of the poorest countries in the world motivated the international community to implement several programs to control or eliminate this scourge. Initially, these involved reducing transmission of the causative agent Onchocerca volvulus through controlling the vector population. When ivermectin was found to be a very effective drug for treating onchocerciasis, the strategy shifted to mass drug administration (MDA) of endemic communities. In some countries, both vector control and ivermectin MDA have been used together. However, traditional vector control methods involve treating rivers in which the black fly vectors breed with insecticides, a process which is expensive, requires trained personnel to administer, and can be ecologically harmful. In this review, we discuss recent research into alternatives to riverine insecticide treatment, which are inexpensive, ecologically less harmful, and can be implemented by the affected communities themselves. These can dramatically reduce vector densities and, when combined with ivermectin MDA, can accelerate the time to elimination when compared to MDA alone.

Simulating a Transmission Assessment Survey: An evaluation of current methods used in determining the elimination of the neglected tropical disease, Lymphatic Filariasis.

INTRODUCTION: The World Health Organization (WHO) recommends Transmission Assessment Surveys (TAS) to determine when an evaluation unit (EU) (a designated population survey area) has achieved elimination of transmission of the vector-borne macroparasitic disease Lymphatic Filariasis (LF). These determinations are based on combining data from multiple survey units within an EU; it is unclear how underlying cluster-level variation influences the outcome of the TAS at EU level. We simulate LF infection distribution in an EU and compare three methods for assessing whether LF elimination has occurred based on currently recommended decision thresholds and sampling methods. METHODS: We simulate an EU divided into clusters of varying size and disease prevalence. We produce 1000 samples according to LF TAS examples and WHO guidelines and compare three decision-making approaches: lot quality assurance sampling (LQAS) (recommended by WHO), one-sided interval estimate (CI), and nth order statistic (MAX). Summary statistics demonstrating the "pass" rate for the EU under different disease transmission conditions are generated using a versatile SAS® macro. RESULTS: As the prevalence of LF decreases, the LQAS and CI approaches produce increased likelihood of a pass outcome for an EU while some cluster units may still have a high likelihood of transmission. The MAX provides an alternative that increases the likelihood of determining a pass only once the whole area has a low likelihood of transmission. LQAS and CI approaches designed to estimate the LF prevalence in the EU miss hotspots that will continue to transmit infection while the MAX approach focuses on identifying clusters with high risk of transmission. CONCLUSIONS: The current TAS methodology has a flaw that may result in false predictions of LF transmission interruption throughout an EU. Modifying the TAS methodology to address results from extreme clusters rather than being based on mean prevalence over an EU will result in greater success for global elimination of LF.

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

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 leading to shorter timelines to extinction, 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.

Continental-scale, data-driven predictive assessment of eliminating the vector-borne disease, lymphatic filariasis, in sub-Saharan Africa by 2020.

BACKGROUND: There are growing demands for predicting the prospects of achieving the global elimination of neglected tropical diseases as a result of the institution of large-scale nation-wide intervention programs by the WHO-set target year of 2020. Such predictions will be uncertain due to the impacts that spatial heterogeneity and scaling effects will have on parasite transmission processes, which will introduce significant aggregation errors into any attempt aiming to predict the outcomes of interventions at the broader spatial levels relevant to policy making. We describe a modeling platform that addresses this problem of upscaling from local settings to facilitate predictions at regional levels by the discovery and use of locality-specific transmission models, and we illustrate the utility of using this approach to evaluate the prospects for eliminating the vector-borne disease, lymphatic filariasis (LF), in sub-Saharan Africa by the WHO target year of 2020 using currently applied or newly proposed intervention strategies. METHODS AND RESULTS: We show how a computational platform that couples site-specific data discovery with model fitting and calibration can allow both learning of local LF transmission models and simulations of the impact of interventions that take a fuller account of the fine-scale heterogeneous transmission of this parasitic disease within endemic countries. We highlight how such a spatially hierarchical modeling tool that incorporates actual data regarding the roll-out of national drug treatment programs and spatial variability in infection patterns into the modeling process can produce more realistic predictions of timelines to LF elimination at coarse spatial scales, ranging from district to country to continental levels. Our results show that when locally applicable extinction thresholds are used, only three countries are likely to meet the goal of LF elimination by 2020 using currently applied mass drug treatments, and that switching to more intensive drug regimens, increasing the frequency of treatments, or switching to new triple drug regimens will be required if LF elimination is to be accelerated in Africa. The proportion of countries that would meet the goal of eliminating LF by 2020 may, however, reach up to 24/36 if the WHO 1% microfilaremia prevalence threshold is used and sequential mass drug deliveries are applied in countries. CONCLUSIONS: We have developed and applied a data-driven spatially hierarchical computational platform that uses the discovery of locally applicable transmission models in order to predict the prospects for eliminating the macroparasitic disease, LF, at the coarser country level in sub-Saharan Africa. We show that fine-scale spatial heterogeneity in local parasite transmission and extinction dynamics, as well as the exact nature of intervention roll-outs in countries, will impact the timelines to achieving national LF elimination on this continent.

A Data-Driven Decision-Support Tool for Population Health Policies.

Epidemiological models are key tools in assessing intervention policies for population health management. Statistical models, fitted with survey or health system data, can be combined with lab and field studies to provide reliable predictions of future population-level disease dynamics distributions and the effects of interventions. All too often, however, the end result of epidemiological modeling and cost-effectiveness studies is in the form of a report or journal paper. These are inherently limited in their coverage of locations, policy options, and derived outcome measures. Here, we describe a tool to support population health policy planning. The tool allows users to explore simulations of various policies, to view and compare interventions spanning multiple variables, time points, and locations. The design's modular architecture, and data representation separate the modeling methods, the outcome measures calculations, and the visualizations, making each component easily replaceable. These advantages make it extremely versatile and suitable for multiple uses.

Biosocial Determinants of Persistent Schistosomiasis among Schoolchildren in Tanzania despite Repeated Treatment.

Schistosomiasis is a parasitic disease endemic to Tanzania and other countries of the global south, which is currently being addressed through preventive chemotherapy campaigns. However, there is growing recognition that chemotherapy strategies will need to be supplemented to sustainably control and eventually eliminate the disease. There remains a need to understand the factors contributing to continued transmission in order to ensure the effective configuration and implementation of supplemented programs. We conducted a cross-sectional questionnaire, to evaluate the biosocial determinants facilitating the persistence of schistosomiasis, among 1704 Tanzanian schoolchildren residing in two districts undergoing a preventive chemotherapeutic program: Rufiji and Mkuranga. A meta-analysis was carried out to select the diagnostic questions that provided a likelihood for predicting infection status. We found that self-reported schistosomiasis continues to persist among the schoolchildren, despite multiple rounds of drug administration.Using mixed effects logistic regression modeling, we found biosocial factors, including gender, socio-economic status, and water, sanitation, and hygiene (WASH)-related variables, were associated with this continued schistosomiasis presence. These findings highlight the significant role that social factors may play in the persistence of disease transmission despite multiple treatments, and support the need not only for including integrated technical measures, such as WASH, but also addressing issues of poverty and gender when designing effective and sustainable schistosomiasis control programs.

Climate, environmental and socio-economic change: weighing up the balance in vector-borne disease transmission.

Arguably one of the most important effects of climate change is the potential impact on human health. While this is likely to take many forms, the implications for future transmission of vector-borne diseases (VBDs), given their ongoing contribution to global disease burden, are both extremely important and highly uncertain. In part, this is owing not only to data limitations and methodological challenges when integrating climate-driven VBD models and climate change projections, but also, perhaps most crucially, to the multitude of epidemiological, ecological and socio-economic factors that drive VBD transmission, and this complexity has generated considerable debate over the past 10-15 years. In this review, we seek to elucidate current knowledge around this topic, identify key themes and uncertainties, evaluate ongoing challenges and open research questions and, crucially, offer some solutions for the field. Although many of these challenges are ubiquitous across multiple VBDs, more specific issues also arise in different vector-pathogen systems.