Spatio-temporal patterns of childhood pneumonia in Bhutan: a Bayesian analysis

Abstract

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.

Identifying socio-ecological drivers of common cold in Bhutan: a national surveillance data analysis

“…Many studies in the past have also reported a high number of common cold cases 48 , 49 and other diseases 50 – 52 during the monsoon season which was also noted in this study. During rainy seasons, it is plausible that many people are restricted to homes where they gather together, during which time infections can spread quickly.…”

“…Another possible reason for an increase in cases following rainfall might be due to contamination of surface water, which is the predominant source of drinking water in the country. Contaminated water and poor sanitation have been associated with high rates of respiratory infections 52 , 53 . An increase in cases of respiratory infections in the aftermath of monsoon flooding has been quite common 54 .…”

“…Initially, we performed a Poisson regression analysis to select covariates, with the number of common cold cases as the dependent variable, and climatic variables with 0, 1, 2 and 3 month lags, as independent variables. We incorporated time lags of up to three months for climatic variables in accordance with the past study 52 . Variables with p < 0.05 and the lowest value of the Akaike Information Criterion (AIC) were selected for inclusion in a multivariable model 69 (Supplementary Table S1 ).…”

Aetiologies and Risk Factors of Prolonged Fever Admission in Samtse Hospital, Bhutan, 2020

“…Secondly, air pollution in southern Bhutan, where Samtse is located, is expected to be higher with increased risk [32][33][34][35]. An earlier study showed that pneumonia was significantly higher in some parts of the southern sub-districts in Bhutan [19]. Lastly, the surface water from streams is the main source of drinking water in rural Bhutan [36].…”

“…In the southern districts of Bhutan, increasing incidence of dengue and scrub typhus are responsible for increasing hospital visits and admissions [14][15][16][17]. Other reported causes of fever admissions include typhoid, chikungunya and respiratory illness [18,19], while the incidence of malaria has been on the decline in recent years [16,20]. In Bhutan's efforts to provide free and quality healthcare to all, there is a need for a better understanding of the epidemiological characteristics and aetiologies of fever and the length of hospital stay among the population living in the sub-tropical region in Bhutan.…”