Malaria is one of the leading causes of morbidity and mortality in Mozambique, which has the fifth highest prevalence in the world. Sussundenga District in Manica Province has documented high P. falciparum incidence at the local rural health center (RHC). This study’s objective was to analyze the P. falciparum temporal variation and model its pattern in Sussundenga District, Mozambique. Data from weekly epidemiological bulletins (BES) was collected from 2015 to 2019 and a time-series analysis was applied. For temporal modeling, a Box-Jenkins method was used with an autoregressive integrated moving average (ARIMA). Over the study period, 372,498 cases of P. falciparum were recorded in Sussundenga. There were weekly and yearly variations in incidence overall (p < 0.001). Children under five years had decreased malaria tendency, while patients over five years had an increased tendency. The ARIMA (2,2,1) (1,1,1) 52 model presented the least Root Mean Square being the most appropriate for forecasting. The goodness of fit was 68.15% for malaria patients less than five years old and 73.2% for malaria patients over five years old. The findings indicate that cases are decreasing among individuals less than five years and are increasing slightly in those older than five years. The P. falciparum case occurrence has a weekly temporal pattern peaking during the wet season. Based on the spatial and temporal distribution using ARIMA modelling, more efficient strategies that target this seasonality can be implemented to reduce the overall malaria burden in both Sussundenga District and regionally.

BackgroundMalaria is still one of the leading causes of mortality and morbidity in Mozambique with little progress in malaria control over the past 20 years. Sussundenga is one of most affected areas. Malaria transmission has a strong association with environmental and socio-demographic factors. The knowledge of sociodemographic factors that affects malaria, may be used to improve the strategic planning for its control and, such studies do not exist in Sussundenga. Hence, the objective of this study is to model the relationship between malaria and sociodemographic factors in Sussundenga, Mozambique. MethodsHouses in the study area were digitalized and enumerated using GoogleEarth ProTM. Hundred houses were randomly selected 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 factors of the participants. Descriptive statistics were analyzed and backward stepwise logistic regression was performed establishing a relationship between positive cases and the factors. The analysis was carried out using SPSS version 20 package. ResultsThe overall P. falciparum prevalence was 31.6 %. Half of the malaria positive cases occurred in age group 5 to 14 years. Previous malaria treatment, population density and age group were significant predictors for the model. The model explained 13.5 % of the variance in malaria positive cases and sensitivity of the final model was 73.3 %. ConclusionIn this area the highest burden of P. falciparum infection was among those t5-14 years old. Malaria infection was related to socio-demographic factors. 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.Trial registrationReview Board (IRB) at the University of Minnesota STUDY00007184 CNBS [IRB00002657]

Background: Malaria is still one of the leading causes of mortality and morbidity in Mozambique with little progress in malaria control over the past 20 years. Sussundenga is one of most affected areas. Malaria transmission has a strong association with environmental and sociodemographic factors. The knowledge of sociodemographic factors that affects malaria, may be used to improve the strategic planning for its control. Currently such studies have not been performed in Sussundenga. Thus, the objective of this study is to model the relationship between malaria and sociodemographic factors in Sussundenga, Mozambique. Methods: Houses in the study area were digitalized and enumerated using Google Earth Pro version 7.3. In this study 100 houses were randomly selected to conduct a community survey of Plasmodium falciparum parasite prevalence using rapid diagnostic test (RDT). During the survey, a questionnaire was conducted to assess the sociodemographic factors of the participants. Descriptive statistics were analyzed and backward stepwise logistic regression was performed establishing a relationship between positive cases and the factors. The analysis was carried out using SPSS version 20 package. Results: The overall P. falciparum prevalence was 31.6%. Half of the malaria positive cases occurred in age group 5 to 14 years. Previous malaria treatment, population density and age group were significant predictors for the model. The model explained 13.5% of the variance in malaria positive cases and sensitivity of the final model was 73.3%. Conclusion: In this area the highest burden of P. falciparum infection was among those aged 5–14 years old. Malaria infection was related to sociodemographic factors. Targeting malaria control at community level can combat the disease more effectively than waiting for cases at health centers. These finding can be used to guide more effective interventions in this region.

BackgroundMalaria is a parasitic borne disease that affects red blood cells. The disease is preventable, detectable and treatable and more common in poor resource settings. It causes socioeconomic impacts, representing a large burden on the revenue of countries where it is endemic. Malaria is undoubtedly one of the main public health concerns impacting on families and the economy in Mozambique. Although the entire population of Mozambique is at risk of malaria, children and pregnant women have higher risk owing to lower immunity. Age category plays a significant important role in malaria occurrence and can affect the course and progression of the disease and correct treatment. Very few studies in pediatric malaria exists in Mozambique and the existing uses a simplistic and coarse grouping. Malaria risk is rarely uniform, whether considering households in a village, villages in a district or districts in a country. The knowledge of malaria pediatric incidence and, the need to evaluate the local heterogeneity by generating malaria risk maps can improve the understanding of pediatric malaria being the objective of this study. Materials and MethodsA retrospective study was conducted using existing malaria positive data from 2018 to 2019 at Rural Sussundenga Hospital (RSH) in Sussundenga municipality. Attributable factor of the disease and incidence were calculated. Proportion of gender, age category and location were tested using G test. For malaria risk mapping, ten malaria factors (anthropic, sociodemographic, climatic and clinic) were used to produce two maps one using malaria incidence and other without. Bioclimatic, Diva GIS 7.4.0 and, Landsat 8 image were used to produce the map.Results and conclusionThe findings revealed that of the, 42,248 patients who visited the local hospital f, 51.2 % tested positive for malaria with an incidence of 45.7 per 100 persons. There is a difference between residential areas in malaria incidence, with both maps showing malaria risk in Nhamazara, Nhamarenza and Unidade communities. This implies that malaria high risk areas seem to be located in high populated areas and areas close to water bodies. Relevant information is provided for effective planning in malaria intervention.

Background: Malaria is a parasitic borne disease that affects red blood cells. The disease is preventable, detectable and treatable and more common in poor resource settings. Malaria is undoubtedly one of the main public health concerns impacting families and the economy in Mozambique. Age category plays a significant important role in malaria occurrence and can affect the course and progression of the disease and correct treatment. Very few studies on pediatric malaria exists in Mozambique and the existing ones use a simplistic and coarse grouping. The knowledge of malaria pediatric incidence and, the need to evaluate the local heterogeneity by generating malaria risk maps can improve the understanding of pediatric malaria being the objective of this study.  Methods: A retrospective study was conducted using existing malaria positive data from 2018 to 2019 at Rural Sussundenga Hospital (RSH) in Sussundenga municipality. Attributable factors of the disease and incidence were calculated. Proportion of gender, age category and location were tested using G test. For malaria risk mapping, ten malaria factors (anthropic, sociodemographic, climatic and clinic) were used to produce two maps: one using malaria incidence and other without. Bioclimatic, Diva GIS 7.4.0 and, Landsat 8 image were used to produce the map.  Results: The findings revealed that of the 42,248 patients who visited the local hospital f, 51.2% tested positive for malaria with an incidence of 45.7 per 100 persons. There is a difference between residential areas in malaria incidence, with both maps showing malaria risk in Nhamazara, Nhamarenza and Unidade communities.   Conclusions: This implies that malaria high risk areas seem to be located in high populated areas and areas close to water bodies. Relevant information is provided for effective planning in malaria intervention.