Pneumonia incidence and determinants in South Punjab, Pakistan (2016-2020): a spatial epidemiological study at...

Pneumonia remains a major cause of morbidity and mortality, particularly in low- and middle-income countries, such as Pakistan. In this study, we aimed to examine the spatial and temporal patterns of pneumonia incidence in South Punjab, Pakistan, and to analyze their association with socio-ecological factors.

We used case report data from the district health information system (DHIS) over the years 2016 to 2020 and applied global and local Moran's I to identify spatial autocorrelation. Furthermore, we employed hot and cold spot analysis to identify significant areas with high and low pneumonia incidence. We used Emerging Hot Spot Analysis (EHSA) and time series clustering to examine shifting and temporal patterns of incidence, respectively. In addition, Generalized Linear Regression (GLR) and Multiscale Geographically Weighted Regression (MGWR) models were used to analyze geographic variation in the association of socio-ecological factors and pneumonia incidence.

Our results showed no significant global clustering of pneumonia incidence. Local Moran's I identified a low-low cluster in DG Khan, while Hot Spot Analysis detected one hot spot in Rajanpur. Multan City showed higher case counts, but this reflected population concentration rather than elevated incidence rates. The temporal analysis confirmed a significant seasonal variation, as well as a decrease in certain Tehsils and an increase in others. Our MGWR model revealed that better female literacy reduced incidence rates of pneumonia, whereas poor housing quality increased incidence rates of pneumonia, particularly in the southwestern areas of South Punjab.

We conclude that socio-ecological variables significantly influenced the incidence of pneumonia in South Punjab, and this association varies substantially over time and space. Our results emphasize the need for locally specific public health interventions to minimize pneumonia incidence in vulnerable populations in Pakistan. Our spatial epidemiological approach can be adapted to other regions of Pakistan and similar socio-ecological contexts in low- and middle-income countries.