Sociodemographic and Economic Traits That Affect Malaria Prevalence in Sussundenga Village, Mozambique.

Abstract

Malaria is still one of the leading causes of mortality and morbidity in Mozambique with the 5 th highest prevalence in the world, with little progress in malaria control over the past 20 years. Sussundenga village is one of most affected areas, and lies along the Zimbabwe border, making evaluation of malaria transmission and control policies integral for regional efforts. The objective of this study was to map and quantify malaria parasite prevalence and model its relationship with sociodemographic and economic traits in Sussundenga Village. Houses in the study area were digitalized and enumerated using GoogleEarth Pro TM . A sample of 125 houses was drawn to conduct a community survey of P. falciparum parasite prevalence using rapid diagnostic test (RDT). During the survey, a questionnaire was conducted to assess the socio-demographic and economic traits of the participants. Descriptive statistics were analyzed and logistic regression was performed to establish the relationship between positive cases and the traits. Using GIS a map the prevalence of malaria was produced. The analysis was carried out using SPSS version 20 package and ArcGis 10.7.1. 358 participants were enrolled, completed the survey, and were tested for malaria. The overall P. falciparum prevalence was 31.6 % and spatiality identified. Half of the malaria positive cases occurred in age group 5 to 14, 40 % more than expected and age group over 24 accounted for 17.6 % the cases, around 50 % less than expected. The model explained 15 % of the variance in malaria positive cases and sensitivity of the final model was 91.8 %. The increase in malaria treated cases, having paid employment, education level and age category, will decrease the probability of malaria positive cases in Sussundenga Village. Conclusion In this area the highest burden of P. falciparum infection was among those 5-14 years old. Malaria infection was related to socio-demographic and economic traits. Targeting malaria control at community level can contributed better than waiting for cases at health centers. These finding can be used to guide more effective interventions in this region.