Statistical modeling of pneumonia transmission rates in Manitoba

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Date
2023-12-13
Authors
Hasan, Md.
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Abstract
Introduction: Pneumonia is a major respiratory infection that significantly strains Manitoba’s healthcare system, resulting a substantial number of hospitalizations and fatalities. Understanding the transmission dynamics and risk factors associated with pneumonia in this population is crucial for targeted interventions. Spatial variability in pneumonia hospitalizations has been observed in Manitoba, where various risk factors contribute to pneumonia infection. Therefore, it is essential to investigate the determinants of pneumonia, including spatial aspects and disease transmission rates. Methods: We applied a spatial Poisson regression model that incorporates the Intrinsic Conditional Autoregressive model to explore region level potential risk factors. To understand the influence of comorbidity, we utilized a mixed-effects Poisson regression model. Our analysis focused on hospital data spanning the years 2015 to 2019, and encompassing 96 Manitoba health regions. Moreover, to investigate disease transition rates, we employed both the Susceptible-Exposed-Infected-Recovery (SEIR) model (excluding reinfection) and the Susceptible-Exposed-Infected-Recovery-Susceptible (SEIRS) model (including reinfection). These compartmental models considered data from both hospital and physician-reported pneumonia cases during August 2017 to July 2018. Results: The raw incidence rate of pneumonia infection exhibited significant variation across different regions, ranging from 2 to 55 cases per 1000 population. After adjusting for potential risk factors, the incidence rate ratios ranged from 0.38 to 6.63, indicating substantial variations in incidence rates among regions. Factors such as age, immigration status, and comorbidities, notably Chronic Obstructive Pulmonary Disease (COPD) and Cardiovascular Disease (CVD), were identified as significant contributors to the risk of pneumonia infection. Conversely, vaccination was found to exert a protective effect, especially among individuals aged over 60 years. The domain-level analysis further demonstrated the significant impact of Inflammatory Bowel Diseases (IBD), COPD and CVD on pneumonia infection. The SEIR and SEIRS models were employed to analyze pneumonia transmission rates, indicated rates of 0.81 and 0.88, respectively. The SEIRS model suggested a reinfection rate of pneumonia was 0.003. The average reproduction number (R0) was calculated at 1.03 for both models, signifying the potential for disease spread in the population. Conclusion: The findings highlighted spatial variation in pneumonia incidence across the 96 health regions in Manitoba. Elder individuals, immigration status, and comorbidities, were identified as significant factors influencing pneumonia infections rates. Vaccination demonstrated a protective effect, particularly among the elderly population. The estimated reinfection interval for pneumonia was determined to be 333 days.
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Keywords
Pneumonia, Transmission rate, Spatial modeling
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