Neglected Tropical Diseases: Infection, Modeling, and Control

Abstract

We survey the current state of a group of parasitic and microbial diseases called the Neglected Tropical Diseases (NTDs). These diseases currently infect a billion people, primarily in socioeconomically depressed areas of the world, are a leading cause of worldwide disability, and are responsible for approximately 534,000 deaths per year. We focus on several subcategories: protozoans, helminthes and bacterial diseases. We identify the populations most at risk from these diseases, and outline symptoms and other disease burdens. We examine the progress being made in controlling NTDs, including the current state of drug development. We also examine mathematical modeling of NTDs. While mathematical modeling is not bound by many of the strictures of access, data collection and infrastructure funding, we nevertheless demonstrate that few NTDs have received much attention from mathematical models, and that some have received no attention at all. Simple mathematical models could contribute significantly to our understanding of these diseases and the efforts required to control them, at very little cost. Further investment in prevention, treatment and awareness of NTDs is urgently warranted.

Regional variation in Ascaris lumbricoides and Trichuris trichiura infections by age cohort and sex: effects of market integration among the indigenous Shuar of Amazonian Ecuador

“…This supports previous findings [11, 14] and suggests that infection peaks during infancy/childhood in populations exposed to endemic parasitic infection and decreases with the development of partial immunity and improved hygiene practices [11, 14]. High infection levels during childhood may have especially severe consequences, including stunted growth and impaired cognitive development, which negatively impact lifelong health [12–15]. Shuar physical growth during childhood has been shown to be slower than that of industrialized populations [35, 36], with Shuar childhood body size demonstrating a close association with MI variables [2].…”

“…Research examining disease patterns among transitioning, vulnerable populations is especially important given the long-term economic and health consequences associated with STH infection (e.g., limited worker productivity and educational attainment due to prolonged infection) [12–15]. Further work is needed to clarify which factors are most strongly linked with STH exposure and better control disease risk, thereby promoting optimal physical health and economic growth among these populations.…”

“…Chronic infection has been associated globally with several negative health consequences, including stunted growth, diarrhea, and nutritional deficiencies [12]. These infections can also result in major economic costs, including decreased work productivity and educational attainment [13–15]. Parasitic infection results in modified immune function (e.g., altered cytokine responses and T-cell profiles), often compromising the efficacy of vaccinations and impairing related health outcomes in STH endemic areas [16].…”

“…Research has consistently demonstrated that school-aged children harbor the highest STH loads [13, 15]. For instance, studies of children in Nigeria, Malaysia, rural China, and Madagascar report prevalence rates of approximately 45–89% for two of the most common STH infections ( Ascaris lumbricoides [ascarids] and Trichuris trichiura [whipworm]), rates that appear to decrease with increasing age (e.g., Nigerian children exhibited T. trichiura prevalence rates 14% higher than older age groups) [17–20].…”

A Multi-Host Agent-Based Model for a Zoonotic, Vector-Borne Disease. A Case Study on Trypanosomiasis in Eastern Province, Zambia

“…A greater understanding of disease transmission in natural and changing ecologies will aid HAT and AAT strategies for disease prevention and control, improving the health and wellbeing of humans, livestock and wildlife. Mathematical modelling of neglected tropical disease (NTD) transmission systems can have a significant impact on intervention strategies and feed into policy formulation [13]. Whether through assessing theoretical interventions [14], investigating vector mortality (e.g.…”