Relationship Between Malaria Cases And Weather Parameters Over Morogoro Municipality.
The study examined the influence of weather parameters on malaria outbreaks over Morogoro Municipality. It is well established that malaria is the leading health problem in Tanzania where it accounts for the most outpatients and inpatients hospital attendances and is among the leading causes of hospital deaths for all ages in the country, and the most vulnerable groups are children under five years and pregnant women. In Morogoro Municipality malaria cases increase during the month of February to May and to a less extent during November to December. Thus the relationship between malaria cases and weather parameters was investigated by applying single mass curve, time series analysis, simple linear regression, multiple linear regression and error analysis. Monthly data for malaria cases from 2007 to 2011 was compared with monthly rainfall, maximum and minimum temperature and relative humidity at 0300Z, 0600Z, 0900Z and 1500Z in order to determine whether malaria epidemics are related with weather parameter as well as to verify if such relation can be used to predict malaria outbreaks. Results indicated that malaria cases prevailed throughout the year and high peaks were reported from February to May and November to December period. Also time series analysis of both malaria cases and weather parameters were increasing from February to May and November to December period. This attributed to the coinciding highest peaks of malaria cases and rainfall, minimum temperature and relative humidity in April and December and lowest peak during the month of July. Simple linear regression showed strong positive relationship as indicated by coefficient of determination, rainfall (65%), maximum temperature (13%) and minimum temperature (50%) respectively. Relative humidity showed a coefficient of determination of 18% at 0300Z, 45% at 0600Z, 29% at 0900Z and 41% at 1500Z. Prediction model was based on multiple regression analysis. Graphical presentations indicated that the model performed well. Its accuracy assessment showed that model deviate little from the mean malaria cases. Also the study noted that five years data was very short to show the accuracy of the model and thus further researches should be done using data of many years. Moreover, data from private hospitals should be included in model development. The relationship observed between malaria cases and weather parameters is the challenge for health sector in Tanzania. More studies need to be done to come up with many strategies that can eradicate malaria over Morogoro Municipality.