This paper describes spatial distribution of Visceral Leishmaniasis (VL) and determines its correlation with climatic factors in an endemic focus in northern and central Tunisia. Data on VL cases in children under five years of age were obtained by consulting medical reports from all Tunisian Pediatric Departments (TPD) during 2006-2016. Three key climatic factors, namely precipitation, continentality index and pluviometric coefficient of Emberger were used as predictor variables to model the VL geographical distribution. Data handling and statistical analysis were performed using R and Arcview GIS software systems. Bayesian local spatial model was employed to analyse the data. The results show a progressive increase in the VL incidence rates in regions with high levels of precipitation, but with low values of both continentality index and pluviometric coefficient of Emberger. A likely explanation of these findings arises from the opposite local effects of climatic factors which tend to cancel each other out in the calculation of the mean parameter estimate over the whole study area. We conclude that using non-local spatial analysis approach leads to misleading epidemiological interpretations, which in turn are of relevance for more efficient and cost-effective resource allocation for control and well manage the spread of VL in the study region and elsewhere in Tunisia.
This study established the correlation between respiratory syncytial virus (RSV) bronchiolitis and climate factors in the area of Sousse, Tunisia, during 13 years (2003-2015), from neonates and children <=?5 years old and hospitalized in Farhat Hached University-Hospital of Sousse. The meteorological data of Sousse including temperature, rainfall, and humidity were obtained. RSV detection was carried out with the direct immunofluorescence assay. The impact of climate factors on viral circulation was statistically analyzed. From 2003 to 2015, the total rate of RSV bronchiolitis accounted for 34.5% and peaked in 2007 and 2013. RSV infection was higher in male cases and pediatric environment (p<0.001) and was detected in 47.3% of hospitalizations in intensive care units. The epidemic of this pathogen started in October and peaked in January (41.6%). When the infectivity of RSV was at its maximum, the monthly average rainfall was high (31 mm) and the monthly average temperature and the monthly average humidity were at their minimum (11 °C and 66%, respectively). RSV activity was negatively correlated with temperature (r?=?-?0.78, p?=?0.003) and humidity (r?=?-?0.62, p?=?0.03). Regression analysis showed that the monthly average temperature fits into a linear model (R(2)?=?61%, p?
