Particulate matter (PM2.5) and diseases: an autoregressive distributed lag (ARDL) technique

Air pollution can be attributed to the reduction in visibility, less agricultural activity, more health issues, and long-term destruction to infrastructure. This paper aimed to examine the validity of association among the Particulate matter (PM2.5) and number of acute upper respiratory infection (ARI) and Asthma (AS) patients using an autoregressive distributed lag (ARDL) approach. This ARDL model study was conducted in Lahore, Pakistan. We used monthly data of ARI and AS patients acquired from Directorate General Health Services Punjab and PM2.5 from Air Visual-IQAir during the period January 2018-August 2019. ARDL bound testing technique was used to investigate the association between number of AS, ARI patients and PM2.5. In the short run, the PM2.5 has substantial positive impact on number of AS patients in Lahore. The values of short-run coefficient depicts that the association between PM2.5 and ARI patients is stronger than AS. The effect of PM2.5 on number of patients in short term is more than that in the long-term. For both AS and ARI, in the long run, PM2.5 has negative impact on number of patients.