Particulate matter (PM2.5) and diseases: an autoregressive distributed lag (ARDL) technique
2021
Qayyum, Fazzal | Mehmood, Usman | Tariq, Salman | Z̤iyāʾulḥaqq, | Nawaz, Hasan
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.
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