Influenza-like illness (ILI) accounts for 500,000 fatalities worldwide yearly. Environmental factors contribute to spread of respiratory infections. This study describes the epidemiological trends of ILI in Cheras, Kuala Lumpur, Malaysia and seeks scientific evidence on ILI activity and environmental factors. Cheras Health District collected ILI surveillance data and the nearest weather station which provided environmental data on mean temperature, humidity, wind speed, cumulative rainfall, particulate matter (PM)10 and PM2.5 levels. A total of 51,245 ILI cases were reported from 1st December 2021 to 30th April 2023. The non-linear relationship between ILI incidence and environmental variables was modelled using the Generalised Additive Model (GAM). The lag time for mean temperature, mean humidity, cumulative rainfall, mean wind speed, PM 10 level, and PM 2.5 level was 2, 3, 3, 3, 0, and 3 days, respectively. The model with the optimal lag better describes ILI case variance (R2=0.5, explained deviance=58%) than the model without lag selection (R2=0.5, explained deviance=57.2%). The Lag Model indicates a significant p-value for PM10 but no significant concurvity between predictor variables. Thus, the final model (R2=0.5, explained deviance=59.2%) has k=15. Higher rainfall, relative humidity, colder temperature, and decreased wind speed increased ILI incidence. PM2.5 and PM10 also contributes to ILI.
Prediction of Influenza-Like Illness Incidence in Cheras, Malaysia based on Environmental Data using the Generalised Additive Model
Abstrak
"Influenza-like illness" (ILI) menyumbang kepada 500,000 kematian di seluruh dunia setiap tahun. Kajian ini menerangkan aliran epidemiologi ILI di Cheras, Kuala Lumpur, Malaysia dan mencari bukti saintifik mengenai aktiviti ILI dan faktor alam sekitar. Daerah Kesihatan Cheras mengumpul data pengawasan ILI dan stesen cuaca terdekat yang menyediakan data persekitaran mengenai suhu purata, kelembapan, kelajuan angin, curah hujan kumulatif, "particulate matter" (PM)10 dan PM2.5 tahap. Sebanyak 51,245 kes ILI dilaporkan pada 1 Disember 2021 hingga 30 April 2023. Perhubungan non-linear antara insiden ILI dan pembolehubah persekitaran telah dimodelkan menggunakan Model Tambahan Umum (GAM). Tempoh penundaan untuk suhu purata, kelembapan rata-rata, curah hujan kumulatif, kelajuan angin purat, tahap PM 10 dan tahap PM 2.5 ialah 2, 3, 3, 3, 0, dan 3 hari, masing-masing. Model dengan lag optimum lebih baik menggambarkan varians kes ILI (R2 = 0.5, penyimpangan yang dijelaskan = 58%) daripada model tanpa pemilihan penundaan (R2 = 0.5, penyimpang yang dijelaskan = 57.2%). Model Lag menunjukkan nilai p yang signifikan untuk PM10 tetapi tidak mempunyai keserasian yang penting antara variabel prediktor. Oleh itu, model akhir (R2 = 0.5, penyimpangan yang dijelaskan = 59.2%) mempunyai k = 15. Hujan yang lebih tinggi, kelembapan relatif, suhu yang lebih sejuk, dan kelajuan angin yang berkurangan meningkatkan kes ILI. PM2.5 dan PM10 juga menyumbang kepada ILI.
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