In Bangladesh respiratory illnesses are one of the leading risk factors for death and disability. Limited access to healthcare services, indoor and outdoor air pollution, large-scale use of smoking materials, allergens, and lack of awareness are among the known leading factors contributing to respiratory illness in Bangladesh. Key initiatives taken by the government to handle respiratory illnesses include, changing of respiratory health policy, building awareness, enhancing healthcare facility, and promoting prevention measures. Despite all these efforts, the number of individuals suffering from respiratory diseases has increased steadily during the recent years. This study aims at examining the distribution pattern of respiratory diseases over space and time using Geographic Information System, which is expected to contribute to the better understand of the factors contributing to respiratory illness development. To achieve the aims of the study two interviews were conducted among patients with respiratory sickness in the medicine and respiratory medicine units of Rajshahi Medical College Hospital between January and April of 2019 and 2020 following the guidelines provided by the Ethics Committee, Department of Geography and Environmental Studies, University of Rajshahi, Bangladesh (ethical approval reference number: 2018/08). Principal component extraction and spatial statistical analyses were performed to identify the key respiratory illnesses and their geographical distribution pattern respectively. The results indicate, during January-February the number of patients was a lot higher compared to March-April. The patients were hospitalized mainly due to four respiratory diseases (chronic obstructive pulmonary disease, asthma, pneumonia, and pulmonary hypertension). Geographical distribution pattern of respiratory disease cases also varied considerably between the years as well as months of the years. This information seems reasonable to elucidate the spatio-temporal distribution of respiratory disease and thus improve the existing prevention, control, and cure practices of respiratory illness of the study area. Approach used in this study to elicit spatio-temporal distribution of repertory disease can easily be implemented in other areas with similar geographical settings and patients' illness information from hospital.
Keywords: Disease mapping; GIS; Geographical distribution; Hot spot analysis; Principal component analysis; Respiratory illness pattern.
© 2023 The Authors.