Pneumonia is one of the top 10 diseases by morbidity in Bhutan. This study aimed to investigate the spatial and temporal trends and risk factors of childhood pneumonia in Bhutan. A multivariable Zero-inflated Poisson regression model using a Bayesian Markov chain Monte Carlo simulation was undertaken to quantify associations of age, sex, altitude, rainfall, maximum temperature and relative humidity with monthly pneumonia incidence and to identify the underlying spatial structure of the data. Overall childhood pneumonia incidence was 143.57 and 10.01 per 1000 persons over 108 months of observation in children aged < 5 years and 5–14 years, respectively. Children < 5 years or male sex were more likely to develop pneumonia than those 5–14 years and females. Each 1 °C increase in maximum temperature was associated with a 1.3% (95% (credible interval [CrI] 1.27%, 1.4%) increase in pneumonia cases. Each 10% increase in relative humidity was associated with a 1.2% (95% CrI 1.1%, 1.4%) reduction in the incidence of pneumonia. Pneumonia decreased by 0.3% (CrI 0.26%, 0.34%) every month. There was no statistical spatial clustering after accounting for the covariates. Seasonality and spatial heterogeneity can partly be explained by the association of pneumonia risk to climatic factors including maximum temperature and relative humidity.
Pneumonia is one of the top 10 diseases by morbity in Bhutan. This study aimed to investigate the spatial and temporal trends and risk factors of pneumonia in Bhutan. A multivariable Zero-inflated Poisson regression using a Bayesian Markov chain Monte Carlo simulation was undertaken to quantify associations of age, sex, rainfall, maximum temperature and relative humidity with monthly pneumonia incidence and identify underlying spatial structure of the data. Overall pneumonia incidence was 96.5 and 4.57 per 1,000 populations over nine years in people aged < 5 years and ≥ 5 years, respectively. Children < 5 years or being a female are more like to get pneumonia than ≥ 5 years and males. A 10mm increase in rainfall and 1°C increase in maximum temperature was associated with a 7.2% (95% (credible interval [CrI] 0.7%, 14.0%) and 28.6% (95% CrI 27.2%, 30.1%) increase in pneumonia cases. A 1% increase in relative humidity was associated with a decrease in the incidence of pneumonia by 8.6% (95% CrI 7.5%, 9.7%). There was no evidence of spatial clustering after accounting for the covariates. Seasonality and spatial heterogeneity can partly be explained by the association of pneumonia risk to climatic factors including rainfall, maximum temperature and relative humidity.
The common cold is a leading cause of morbidity and contributes significantly to the health costs in Bhutan. The study utilized multivariate Zero-inflated Poisson regression in a Bayesian framework to identify climatic variability and spatial and temporal patterns of the common cold in Bhutan. There were 2,480,509 notifications of common cold between 2010 and 2018. Children aged < 15 years were twice (95% credible interval [CrI] 2.2, 2.5) as likely to get common cold than adults, and males were 12.4% (95 CrI 5.5%, 18.7%) less likely to get common cold than females. A 10 mm increase in rainfall lagged one month, and each 1 °C increase of maximum temperature was associated with a 5.1% (95% CrI 4.2%, 6.1%) and 2.6% (95% CrI 2.3%, 2.8%) increase in the risk of cold respectively. An increase in elevation of 100 m and 1% increase in relative humidity lagged three months were associated with a decrease in risk of common cold by 0.1% (95% CrI 0.1%, 0.2%) and 0.3% (95% CrI 0.2%, 0.3%) respectively. Seasonality and spatial heterogeneity can partly be explained by the association of common cold to climatic variables. There was statistically significant residual clustering after accounting for covariates. The finding highlights the influence of climatic variables on common cold and suggests that prioritizing control strategies for acute respiratory infection program to subdistricts and times of the year when climatic variables are associated with common cold may be an effective strategy.
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