Agriculture, development and malaria in rural Uganda

While malaria remains a major global public health problem, total annual incidence fell by 30% during 2000–2013, largely due to the scale–up of long–lasting insecticide–treated nets and indoor residual spraying. In the future, sustainable methods of control and elimination are needed to maintain this progress. Since malaria is associated with poverty, malaria control and economic development can be mutually supportive. This thesis tests specific hypotheses relating to the causal pathways between poverty and malaria, to identify potential routes to controlling malaria alongside development. Two systematic reviews found that in sub-Saharan Africa: (1) parasite prevalence and clinical malaria incidence are on average halved in the wealthiest children, compared to the poorest within a community and (2) parasite prevalence and clinical malaria incidence are on average halved in residents of modern housing, compared to traditional housing. In-depth interviews and cross-sectional surveys collected socioeconomic information for all children aged six months to 10 years living in 100 households, who were followed for 36 months in Nagongera, an agrarian and highly endemic setting in rural Uganda. Analyses of the relationships between socioeconomic position (SEP), potential determinants of SEP and malaria found that: (3) relative success in smallholder agriculture was associated with higher SEP, (4) human biting rate (HBR) and parasite prevalence were approximately halved in children of highest SEP, compared to the poorest, (5) wealth indices, income and education were more sensitive indicators of socioeconomic inequalities in malaria risk than occupation, (6) HBR and parasite prevalence were halved in modern housing, compared to traditional housing and (7) house quality may partly explain the association between SEP and malaria. Together, these studies indicate that housing improvements and agricultural development interventions to reduce poverty merit further investigation as ‘intersectoral’ interventions against malaria

The associations between malaria, interventions, and the environment: a systematic review and meta-analysis.

BACKGROUND: Malaria transmission is driven by multiple factors, including complex and multifaceted connections between malaria transmission, socioeconomic conditions, climate and interventions. Forecasting models should account for all significant drivers of malaria incidence although it is first necessary to understand the relationship between malaria burden and the various determinants of risk to inform the development of forecasting models. In this study, the associations between malaria risk, environmental factors, and interventions were evaluated through a systematic review. METHODS: Five electronic databases (CAB Abstracts, EMBASE, Global Health, MEDLINE and ProQuest Dissertations & Theses) were searched for studies that included both the effects of the environment and interventions on malaria within the same statistical model. Studies were restricted to quantitative analyses and health outcomes of malaria mortality or morbidity, outbreaks, or transmission suitability. Meta-analyses were conducted on a subset of results using random-effects models. RESULTS: Eleven studies of 2248 potentially relevant articles that met inclusion criteria were identified for the systematic review and two meta-analyses based upon five results each were performed. Normalized Difference Vegetation Index was not found to be statistically significant associated with malaria with a pooled OR of 1.10 (95% CI 0.07, 1.71). Bed net ownership was statistically associated with decreasing risk of malaria, when controlling for the effects of environment with a pooled OR of 0.75 (95% CI 0.60, 0.95). In general, environmental effects on malaria, while controlling for the effect of interventions, were variable and showed no particular pattern. Bed nets ownership, use and distribution, have a significant protective effect while controlling for environmental variables. CONCLUSIONS: There are a limited number of studies which have simultaneously evaluated both environmental and interventional effects on malaria risk. Poor statistical reporting and a lack of common metrics were important challenges for this review, which must be addressed to ensure reproducibility and quality research. A comprehensive or inclusive approach to identifying malaria determinants using standardized indicators would allow for a better understanding of its epidemiology, which is crucial to improve future malaria risk estimations

Assessing the health benefits of development interventions

Biomedical interventions, such as therapeutics, vaccines and insecticides, are alone insufficient to achieve Sustainable Development Goal (SDG) 3—healthy lives and wellbeing for all ages. We also need development interventions to tackle the underlying determinants of ill-health by reducing deprivation and improving living conditions and the environment. This recognition formed the bedrock of early public health, from housing improvements and clean water provision in 19th century Europe and North America, to house screening for malaria elimination in the USA and water management for historical vector control in Italy, Sri Lanka, Panama and Zambia. Today, development interventions are a basic human right and ever more critical in response to rapid population growth, urbanisation and climate change

Evidence-based vector control? Improving the quality of vector control trials.

Vector-borne diseases (VBDs) such as malaria, dengue, and leishmaniasis cause a high level of morbidity and mortality. Although vector control tools can play a major role in controlling and eliminating these diseases, in many cases the evidence base for assessing the efficacy of vector control interventions is limited or not available. Studies assessing the efficacy of vector control interventions are often poorly conducted, which limits the return on investment of research funding. Here we outline the principal design features of Phase III vector control field studies, highlight major failings and strengths of published studies, and provide guidance on improving the design and conduct of vector control studies. We hope that this critical assessment will increase the impetus for more carefully considered and rigorous design of vector control studies

Why is malaria associated with poverty? Findings from a cohort study in rural Uganda

Background Malaria control and sustainable development are linked, but implementation of ‘multisectoral’ intervention is restricted by a limited understanding of the causal pathways between poverty and malaria. We investigated the relationships between socioeconomic position (SEP), potential determinants of SEP, and malaria in Nagongera, rural Uganda. Methods Socioeconomic information was collected for 318 children aged six months to 10 years living in 100 households, who were followed for up to 36 months. Mosquito density was recorded using monthly light trap collections. Parasite prevalence was measured routinely every three months and malaria incidence determined by passive case detection. First, we evaluated the association between success in smallholder agriculture (the primary livelihood source) and SEP. Second, we explored socioeconomic risk factors for human biting rate (HBR), parasite prevalence and incidence of clinical malaria, and spatial clustering of socioeconomic variables. Third, we investigated the role of selected factors in mediating the association between SEP and malaria. Results Relative agricultural success was associated with higher SEP. In turn, high SEP was associated with lower HBR (highest versus lowest wealth index tertile: Incidence Rate Ratio 0.71, 95 % confidence intervals (CI) 0.54–0.93, P = 0.01) and lower odds of malaria infection in children (highest versus lowest wealth index tertile: adjusted Odds Ratio 0.52, 95 % CI 0.35–0.78, P = 0.001), but SEP was not associated with clinical malaria incidence. Mediation analysis suggested that part of the total effect of SEP on malaria infection risk was explained by house type (24.9 %, 95 % CI 15.8–58.6 %) and food security (18.6 %, 95 % CI 11.6–48.3 %); however, the assumptions of the mediation analysis may not have been fully met. Conclusion Housing improvements and agricultural development interventions to reduce poverty merit further investigation as multisectoral interventions against malaria. Further interdisplinary research is needed to understand fully the complex pathways between poverty and malaria and to develop strategies for sustainable malaria control

Measuring socioeconomic inequalities in relation to malaria risk: a comparison of metrics in rural Uganda

ocioeconomic position (SEP) is an important risk factor for malaria, but there is no consensus on how to measure SEP in malaria studies. We evaluated the relative strength of four indicators of SEP in predicting malaria risk in Nagongera, Uganda. 318 children resident in 100 households were followed for 36 months to measure parasite prevalence routinely every three months and malaria incidence by passive case detection. Household SEP was determined using: (1) two wealth indices, (2) income, (3) occupation and (4) education. Wealth Index I (reference) included only asset ownership variables. Wealth Index II additionally included food security and house construction variables, which may directly affect malaria. In multivariate analysis, only Wealth Index II and income were associated with the human biting rate, only Wealth Indices I and II were associated with parasite prevalence and only caregiver’s education was associated with malaria incidence. This is the first evaluation of metrics beyond wealth and consumption indices for measuring the association between SEP and malaria. The wealth index still predicted malaria risk after excluding variables directly associated with malaria, but the strength of association was lower. In this setting, wealth indices, income and education were stronger predictors of socioeconomic differences in malaria risk than occupation

Insights from agriculture for the management of insecticide resistance in disease vectors

Key to contemporary management of diseases such as malaria, dengue, and filariasis is control of the insect vectors responsible for transmission. Insecticide-based interventions have contributed to declines in disease burdens in many areas, but this progress could be threatened by the emergence of insecticide resistance in vector populations. Insecticide resistance is likewise a major concern in agriculture, where insect pests can cause substantial yield losses. Here, we explore overlaps between understanding and managing insecticide resistance in agriculture and in public health. We have used the Global Plan for Insecticide Resistance Management in malaria vectors, developed under the auspices of the World Health Organization Global Malaria Program, as a framework for this exploration because it serves as one of the few cohesive documents for managing a global insecticide resistance crisis. Generally, this comparison highlights some fundamental differences between insect control in agriculture and in public health. Moreover, we emphasize that the success of insecticide resistance management strategies is strongly dependent on the biological specifics of each system. We suggest that the biological, operational, and regulatory differences between agriculture and public health limit the wholesale transfer of knowledge and practices from one system to the other. Nonetheless, there are some valuable insights from agriculture that could assist in advancing the existing Global Plan for Insecticide Resistance Management framework

Recommendations for building out mosquito-transmitted diseases in sub-Saharan Africa: the DELIVER mnemonic

In sub-Saharan Africa, most transmission of mosquito-transmitted diseases, such as malaria or dengue, occurs within or around houses. Preventing mosquito house entry and reducing mosquito production around the home would help reduce the transmission of these diseases. Based on recent research, we make key recommendations for reducing the threat of mosquito-transmitted diseases through changes to the built environment. The mnemonic, DELIVER, recommends the following best practices: (i) Doors should be screened, self-closing and without surrounding gaps; (ii) Eaves, the space between the wall and roof, should be closed or screened; (iii) houses should be Lifted above the ground; (iv) Insecticide-treated nets should be used when sleeping in houses at night; (v) houses should be Ventilated, with at least two large-screened windows to facilitate airflow; (vi) Environmental management should be conducted regularly inside and around the home; and (vii) Roofs should be solid, rather than thatch. DELIVER is a package of interventions to be used in combination for maximum impact. Simple changes to the built environment will reduce exposure to mosquito-transmitted diseases and help keep regions free from these diseases after elimination. This article is part of the theme issue ‘Novel control strategies for mosquito-borne diseases'