Spatial – temporal modeling of malaria cases in elimination phase in Kerman province, Southeast of Iran, 2016-2018

Background: Malaria is a main vector-borne public health problem in Iran, particularly in the eastern and south-eastern areas. The malaria incidence rate is strongly associated with factors such as massive displacements, famine, lack of efficient disease surveillance, and environmental conditions. Recently malaria was eliminated in Kerman province.Objectives: The aim of this study was to determine the situation of the disease and provide the risk map for the area in Kerman province, Southeast of Iran, among 2016 - 2018.Materials and Methods: In this cross-sectional study, the data of all 74 registered new cases malaria among 2016-2018, which all are imported cases, were studied. To model spatial relationship between climatic conditions and distribution of malaria, ArcGIS 10.5 was used. Hot spots were obtained using evidence-based weighting method for transmission risk. Environmental factors including temperature, relative humidity and altitude were combined by weighted multi criteria evaluation for mapping malaria hazard area at the district level Results: Two strata are described based on malaria hot spots. Our results reveal that the disease mainly occurs in north (Rafsanjan) and south (Jiroft) of the study area. Although the temperature and relative humidity are the most important climatic factors for explaining API, since all cases were imported, these factors are not relevant in this study. This model explained only 0.43 of cases spatial variation (R2=0.43).Conclusion: The non-climatic factors such as socioeconomic, lifestyle and the neighborhood position of this province with Afghanistan and Pakistan also should be considered in epidemiological survey of malaria in Kerman. The health policy makers in this province should pay more attention to the areas with high temperature, elevation, and humidity, as well as, low rainfall districts with population movement from eastern part of country

کلیدواژه ها:

Malaria ، Spatial ، Temporal ، Kerman ، Southeast