Sunshine, rainfall, humidity and child pneumonia in the tropics: time-series analyses

Impact of hot and cold nights on pneumonia hospitalisations in children under five years: Evidence from low-, middle-, and high-income countries

BACKGROUND

Studies have shown that abnormal temperature at night is a risk factor for respiratory health. However, there is limited evidence on the impact of hot and cold nights on cause-specific diseases such as pneumonia, which is a leading cause of morbidity and mortality in children.

METHODS

We collected daily data on pneumonia hospitalisations in children under five years from 2011 to 2017 in three low-, middle- and high-income countries (Bangladesh, China, and Australia). The intensity of hot and cold nights was measured by excess temperature. A space-time-stratified case-crossover analysis was used to estimate the association between hot and cold nights and childhood pneumonia hospitalisations. We further estimated the fraction of childhood pneumonia hospitalisations attributable to hot and cold nights.

RESULTS

Both hot and cold nights were associated with an increased risk of hospitalisations for childhood pneumonia in low-, middle-, and high-income countries, with a greater disease burden from hot nights. Specifically, the fraction of childhood pneumonia attributable to hot nights was the largest in Australia [21.2%, 95% confidence interval (CI): 11.8%-28.1%], followed by Bangladesh (15.2%, 95% CI: 4.1%-23.8%) and China (2.7%, 95% CI: 0.4%-4.7%). Additionally, the fraction of childhood pneumonia attributable to cold nights was 1.3% (95% CI: 0.4%-2.0%) in Bangladesh and 0.4% (95% CI: 0.1%-0.7%) in China.

CONCLUSION

This multi-country study suggests that hot and cold nights are not only associated with a higher risk of pneumonia hospitalisations in children but also responsible for substantial fraction of hospitalisations, with a greater impact from hot nights.

Extreme temperatures increase the risk of pediatric pneumonia: a systematic review and meta-analysis

Introduction

The impact of climate change on ambient temperatures threatens to worsen pediatric pneumonia-related outcomes considerably. This study examined the associations of temperature variation and extreme temperature with pediatric pneumonia-related events using a meta-analysis.

Methods

We systematically searched PubMed, Medline, Embase, and Web of Science databases for relevant literature, and the quality of evidence was assessed. Fixed and random-effects meta-analyses were performed to calculate the pooled relative risks (RRs) of the associations with pneumonia-related events.

Results

We observed that a 1°C temperature variation increased the RR of pneumonia events by 1.06-fold (95% confidence interval (CI): 1.03-1.10). A 1°C temperature variation increased the RR by 1.10-fold of the pediatric pneumonia hospital admissions (95% CI: 1.00-1.21) and 1.06-fold of the pediatric pneumonia emergency department visits (95% CI: 1.01-1.10). Extreme cold increased the RR by 1.25-fold of the pediatric pneumonia events (95% CI: 1.07-1.45). A 1°C temperature variation increased the RR of pneumonia events in children by 1.19-fold (95% CI: 1.08-1.32), girls by 1.03-fold (95% CI: 1.02-1.05), and in temperate climate zones by 1.07-fold (95% CI: 1.03-1.11). Moreover, an increase in extreme cold increased the RR of pneumonia events in children by 2.43-fold (95% CI: 1.72-3.43), girls by 1.96-fold (95% CI: 1.29-2.98) and in temperate climate zones by 2.76-fold (95% CI: 1.71-4.47).

Conclusion

Our study demonstrated that pediatric pneumonia events are more prevalent among children, particularly girls, and individuals residing in temperate climate zones. Climate change represents an emergent public health threat, affecting pediatric pneumonia treatment and prevention..

Systematic Review Registration

PROSPERO (CRD42022378610).

Increasing ratio of opportunistic infections associated with sunshine exposure and economic level burdening Chinese inflammatory bowel disease hospitalized patients: the first nationwide survey from 2014 to 2019

BACKGROUND

The rising prevalence of opportunistic infections (OIs) in inflammatory bowel disease (IBD) in conjunction with the use of biologics/immunosuppressive agents has garnered attention. However, there is a dearth of research on OIs in Mainland China. This study seeks to evaluate the national ratio trend of OIs in IBD and elucidate the influence of economic and climate factors on IBD patients with OIs and their outcomes.

METHODS

The nationwide data was obtained from the Inpatient medical record home page via the Health Statistics and Information Reporting System (HSRS). Patients diagnosed with IBD were enlisted for participation, and their demographic and clinical information, encompassing infection type, surgical procedures, and expenses, were gathered. The National Bureau of Statistics provided data on monthly sunshine exposure hours and yearly Gross Domestic Product (GDP).

RESULTS

Findings indicate that between 2014 and 2019, a total of 381,752 patients with IBD were admitted to hospitals, with 364,249 patients lacking OIs and 17,503 patients presenting with OIs. The annual proportion of OIs exhibited an upward trend, rising from 3.54% in 2014 to 4.81% in 2019. There was a significant correlation observed between individuals who identified as male, those who visited hospitals in southern regions, or those originating from areas with lower GDP or shorter sunshine exposure hours, and a higher incidence of OIs. Among patients diagnosed with either Crohn's disease (CD) or ulcerative colitis (UC), Clostridium difficile was found to be the most prevalent infection, followed by Epstein-Barr virus and cytomegalovirus. Furthermore, the occurrence of OIs was found to be associated with an increased rate of surgical interventions in UC patients.

CONCLUSIONS

The rising prevalence of OIs among hospitalized patients with IBD necessitates heightened attention towards mitigating associated risk factors, particularly among IBD patients residing in less developed regions or experiencing limited exposure to sunlight. This approach aims to minimize hospital stays and associated costs.

Differentiating the impacts of ambient temperature on pneumonia mortality of various infectious causes: a nationwide, individual-level, case-crossover study

BACKGROUND

It remains unknown how ambient temperature impact pneumonia of various infectious causes.

METHODS

Based on the national death registry covering all counties in Chinese mainland, we conducted an individual-level case-crossover study in China from 2013 to 2019. Exposures were assigned at residential addresses for each decedent. Conditional logistic regression model combined with distributed lag non-linear models were used to estimate the exposure-response associations. The attributable fractions due to non-optimum temperature were calculated after accounting for spatial and temporal patterns for the excess risks.

FINDINGS

The exposure-response curves were inversely J-shaped with both low and high temperature increasing the risks, and the effect of low temperature was stronger. Extremely low temperature was associated with higher magnitude of influenza-related pneumonia [relative risk (RR): 2.46, 95% confidence interval (CI): 1.62-3.74], than viral pneumonia (RR: 1.89, 95% CI: 1.55-2.30) and bacterial pneumonia (RR: 1.81, 95% CI: 1.56-2.09). The magnitudes of RRs associated with extremely high temperature were similar among the three categories of pneumonia. The mortality attributable fraction for influenza-related pneumonia (29.78%) was the highest. The effects were stronger in people of low education level or residence in the north.

INTERPRETATION

This nationwide study presents findings on the varied risk and burden of pneumonia mortality of various infectious causes, and highlights the susceptibility of influenza-related pneumonia to ambient low temperature.

FUNDING

This study is supported by the National Key Research and Development Program (2022YFC3702701), the Shanghai Municipal Science and Technology Commission (21TQ015) and Shanghai International Science and Technology Partnership Project (21230780200).

Nonlinear and Multidelayed Effects of Meteorological Drivers on Human Respiratory Syncytial Virus Infection in Japan

In this study, we aimed to characterize the nonlinear and multidelayed effects of multiple meteorological drivers on human respiratory syncytial virus (HRSV) infection epidemics in Japan. The prefecture-specific weekly time-series of the number of newly confirmed HRSV infection cases and multiple meteorological variables were collected for 47 Japanese prefectures from 1 January 2014 to 31 December 2019. We combined standard time-series generalized linear models with distributed lag nonlinear models to determine the exposure-lag-response association between the incidence relative risks (IRRs) of HRSV infection and its meteorological drivers. Pooling the 2-week cumulative estimates showed that overall high ambient temperatures (22.7 °C at the 75th percentile compared to 16.3 °C) and high relative humidity (76.4% at the 75th percentile compared to 70.4%) were associated with higher HRSV infection incidence (IRR for ambient temperature 1.068, 95% confidence interval [CI], 1.056-1.079; IRR for relative humidity 1.045, 95% CI, 1.032-1.059). Precipitation revealed a positive association trend, and for wind speed, clear evidence of a negative association was found. Our findings provide a basic picture of the seasonality of HRSV transmission and its nonlinear association with multiple meteorological drivers in the pre-HRSV-vaccination and pre-coronavirus disease 2019 (COVID-19) era in Japan.

Forecasting upper respiratory tract infection burden using high-dimensional time series data and forecast combinations

Upper respiratory tract infections (URTIs) represent a large strain on primary health resources. To mitigate URTI transmission and public health burdens, it is important to pre-empt and provide forward guidance on URTI burden, while taking into account various facets which influence URTI transmission. This is so that appropriate public health measures can be taken to mitigate strain on primary care resources. This study describes a new approach to forecasting URTIs which can be used for national public health resource planning. Specifically, using environmental and disease data comprising more than 1000 dimensions, we developed sub-models which optimizes model explainability, in-sample model fit, predictive accuracy and combines many weaker predictors over a 2-month time horizon to generate direct, point forecasts over a 1-8 week ahead forecast horizon. Predictive performance was evaluated using rolling out-of-sample forecast assessment within both periods with/without structural breaks in transmission over the period of 2012-2022. We showed that forecast combinations of 5 other forecasting models had better and more consistent predictive performance than other modelling approaches, over periods with and without structural breaks in transmission dynamics. Furthermore, epidemiological analysis on high dimensional data was enabled using post-selection inference, to show the dynamic association between lower temperature, increases in past relative humidity and absolute humidity and increased URTIs attendance. The methods proposed can be used for outbreak preparedness and guide healthcare resource planning, in both stable periods of transmission and periods where structural breaks in data occur.

Association of climate factors and air pollutants with pneumonia incidence in Lampang province, Thailand: findings from a 12-year longitudinal study

This study attempted to understand the associations between pneumonia, climate, and environmental air pollutants in Thailand. A 12-year longitudinal study was performed between 2003 and 2014 in Lampang province, the Northern region of Thailand. Spearman correlation and negative binomial regression modelling were used to explore the relationships between climate factors and environmental air pollutants and pneumonia incidence. Spearman correlation shows that pneumonia incidence was positively correlated with humidity and negatively correlated with temperature, NO₂, and O₃. The regression modelling produced a series of models to predict pneumonia incidence based on information on climate and air quality. The result of the models shows that humidity and PM₁₀ were associated with pneumonia incidence. To better protect the health, public health policy and risk assessment approach for pneumonia incidence should include considerations of the effect of air pollution. This result can be used for further intervention to take care of human health.

Climate impacts on air quality and child health and wellbeing: Implications for Oceania

Despite the enormous gains in reducing child mortality resulting from the United Nations Millennium Development Goals, in some ways children's future wellbeing has never been under greater threat. Climate and environmental change, primarily driven by poor air quality, represents a major threat to child health and wellbeing, through both direct and indirect effects. Climate change has multiple environmental consequences impacting negatively on child health and wellbeing, including increases in ambient temperature, rising atmospheric carbon dioxide (CO₂₎ , altered distribution of rainfall, ocean warming, rising sea level and more frequent and severe adverse weather events. Multiple pathways link these exposures to a wide variety of adverse health outcomes. Countries in Oceania are especially likely to be subjected to the effects of increases in ambient temperature, altered distribution of rainfall, ocean warming and sea level rise. These changes pose a significant risk to children and provide a moral imperative for us to act to protect child health.

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

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.

Multifractal analysis of air and soil temperatures

Air and soil temperatures are important agrometeorological variables with several applications. Understanding the complex behavior of air and soil temperatures, as well as their interaction, will help in agricultural planning. Multifractal detrended fluctuation and multifractal cross-correlation analysis of air and soil temperatures were carried out in three locations (Akure, Abuja, and Bauchi) within a tropical country, Nigeria. Monthly and annual air and soil temperatures measured at 5 min intervals for a period of 1 year were obtained and analyzed for multifractality. There is evidence of seasonal dependence in the multifractal behavior of monthly soil temperature. Monthly temperatures (air and soil) were found to have higher degrees of multifractality than annual temperatures. Furthermore, latitudinal dependence was observed in the multifractal behavior of air and soil temperatures. The cross-correlation between air and soil temperatures also shows multifractality with persistence at the monthly scale and anti-persistence at the annual scale. This work has shed light on the complex relationship between air and soil temperatures, and the results will be useful in modeling the two variables.

Winter Is Coming: A Southern Hemisphere Perspective of the Environmental Drivers of SARS-CoV-2 and the Potential Seasonality of COVID-19

SARS-CoV-2 virus infections in humans were first reported in December 2019, the boreal winter. The resulting COVID-19 pandemic was declared by the WHO in March 2020. By July 2020, COVID-19 was present in 213 countries and territories, with over 12 million confirmed cases and over half a million attributed deaths. Knowledge of other viral respiratory diseases suggests that the transmission of SARS-CoV-2 could be modulated by seasonally varying environmental factors such as temperature and humidity. Many studies on the environmental sensitivity of COVID-19 are appearing online, and some have been published in peer-reviewed journals. Initially, these studies raised the hypothesis that climatic conditions would subdue the viral transmission rate in places entering the boreal summer, and that southern hemisphere countries would experience enhanced disease spread. For the latter, the COVID-19 peak would coincide with the peak of the influenza season, increasing misdiagnosis and placing an additional burden on health systems. In this review, we assess the evidence that environmental drivers are a significant factor in the trajectory of the COVID-19 pandemic, globally and regionally. We critically assessed 42 peer-reviewed and 80 preprint publications that met qualifying criteria. Since the disease has been prevalent for only half a year in the northern, and one-quarter of a year in the southern hemisphere, datasets capturing a full seasonal cycle in one locality are not yet available. Analyses based on space-for-time substitutions, i.e., using data from climatically distinct locations as a surrogate for seasonal progression, have been inconclusive. The reported studies present a strong northern bias. Socio-economic conditions peculiar to the 'Global South' have been omitted as confounding variables, thereby weakening evidence of environmental signals. We explore why research to date has failed to show convincing evidence for environmental modulation of COVID-19, and discuss directions for future research. We conclude that the evidence thus far suggests a weak modulation effect, currently overwhelmed by the scale and rate of the spread of COVID-19. Seasonally modulated transmission, if it exists, will be more evident in 2021 and subsequent years.

Epidemiological analysis of association between lagged meteorological variables and pneumonia in wet-dry tropical North Australia, 2006-2016

Pneumonia accounts for 1.5% of all overnight hospital admission in Australia. We investigated the nonlinear and delay effect of weather (temperature and rainfall) on pneumonia. This study was based on a large cohort of inpatients that were hospitalized due to pneumonia between 2006 and 2016. Cases were identified using the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD10-AM) codes J10.0*-J18.0*. A time-varying distributed lag nonlinear model was used to estimate the burden of the disease attributable to varying weather-lag pneumonia relationships and identify vulnerable groups. The relative risk (presented as logRR) associated with temperature was immediate and highest in late winter at the lowest temperature of 16 °C (logRR = 1.13, 95% confidence intervals (CI): 0.59, 1.66). The cumulative effect over the lag range 0-8 weeks revealed two peaks for low (12 mm, logRR = 0.73, 95% CI: 0.32, 1.13) and moderately high rainfall (51 mm) with logRR of 1.15 (95% CI: 0.10, 2.20). A substantial number, 22.50% (95% empirical CI: 1.83, 34.68), of pneumonia cases were attributable to temperature (mostly due to moderate low temperatures). Females and indigenous (Aboriginal and Torres Strait Islander) patients were particularly vulnerable to the impact of temperature-related pneumonia. In this study, we highlighted the delayed effects and magnitude of burden of pneumonia that is associated with low temperature and rainfall. The findings in this study can inform a better understanding of the health implications and burden associated with pneumonia to support discussion-making in healthcare and establish a strategy for prevention and control of the disease among vulnerable groups.

Weather factors, PCV intervention and childhood pneumonia in rural Bangladesh

Available evidence is limited on the association between weather factors and childhood pneumonia, especially in developing countries. This study examined the effects of weather variability on childhood pneumonia after the introduction of pneumococcal conjugate vaccines (PCV) intervention in rural Bangladesh. Data on pneumonia cases and weather variables (temperature and relative humidity) between the 1st January 2012 and the 31st December 2016 were collected from Matlab Hospital, International Centre for Diarrhoeal Disease Research, Bangladesh, and Bangladesh Meteorological Department, respectively. Time series cross-correlation functions were applied to identify the time lags of the effect of each weather factor on pneumonia. Generalized linear regression model with Poisson link was used to quantify the association between weather factors and childhood pneumonia after adjustment of PCV intervention. The annual incidence rate of pneumonia reduced from 5691/100,000 to 2000/100,000 after PCV intervention. Generalized linear regression model suggested that temperature had a negative association with childhood pneumonia (relative risk, 0.985; 95% confidence interval (CI), 0.974-0.997), and PCV intervention was a protective factor with the relative risk estimate of 0.489 (95% CI, 0.435-0.551). However, no substantial association was found with relative humidity. PCV intervention appeared protective against childhood pneumonia, and temperature might be associated with this disease in children. Our findings may help inform public health policy, including the potential of development of early warning systems based on weather factors and PCV for the control and prevention of pneumonia in lower middle-income country like Bangladesh.

Reducing respiratory syncytial virus (RSV) hospitalization in a lower-income country by vaccinating mothers-to-be and their households

Respiratory syncytial virus is the leading cause of lower respiratory tract infection among infants. RSV is a priority for vaccine development. In this study, we investigate the potential effectiveness of a two-vaccine strategy aimed at mothers-to-be, thereby boosting maternally acquired antibodies of infants, and their household cohabitants, further cocooning infants against infection. We use a dynamic RSV transmission model which captures transmission both within households and communities, adapted to the changing demographics and RSV seasonality of a low-income country. Model parameters were inferred from past RSV hospitalisations, and forecasts made over a 10-year horizon. We find that a 50% reduction in RSV hospitalisations is possible if the maternal vaccine effectiveness can achieve 75 days of additional protection for newborns combined with a 75% coverage of their birth household co-inhabitants (~7.5% population coverage).

Meteorological factors affecting respiratory syncytial virus infection: A time-series analysis

INTRODUCTION

Respiratory syncytial virus (RSV) infection is a major cause of hospitalization in children. Meteorological factors are known to influence seasonal RSV epidemics, but the relationship between meteorological factors and RSV infection in children is not well understood. We aimed to explore the relationship between meteorological factors and RSV infections among hospitalized children, using different statistical models.

METHODS

We conducted a retrospective review concerning children with RSV infections admitted to a tertiary pediatric hospital in Wenzhou, China, between January 2008 and December 2017. The relationship between meteorological factors (average daily temperatures, average daily relative humidity, rainfall, rainfall days, and wind speed) and the incidence of RSV in hospitalized children was analyzed using three time-series models, namely an autoregressive integrated moving average (ARIMA) model, a generalized additive model (GAM), and a least absolute shrinkage and selection operator (LASSO)-based model.

RESULTS

In total, 15 858 (17.6%) children tested positive for RSV infection. The ARIMA model revealed a marked seasonal pattern in the RSV detection rate, which peaked in winter and spring. The model was a good predictor of RSV incidence (R² : 83.5%). The GAM revealed that a lower temperature and higher wind speed preceded increases in RSV detection. The LASSO-based model revealed that temperature and relative humidity were negatively correlated with RSV detection.

CONCLUSIONS

Seasonality of RSV infection in hospitalized children correlated strongly with temperature. The LASSO-based model can be used to predict annual RSV epidemics using weather forecast data.

Scoping Review of Climate Change and Health Research in the Philippines: A Complementary Tool in Research Agenda-Setting

The impacts of climate change on human health have been observed and projected in the Philippines as vector-borne and heat-related diseases have and continue to increase. As a response, the Philippine government has given priority to climate change and health as one of the main research funding topics. To guide in identifying more specific research topics, a scoping review was done to complement the agenda-setting process by mapping out the extent of climate change and health research done in the country. Research articles and grey literature published from 1980 to 2017 were searched from online databases and search engines, and a total of 34 quantitative studies were selected. Fifty-three percent of the health topics studied were about mosquito-borne diseases, particularly dengue fever. Seventy-nine percent of the studies reported evidence of positive associations between climate factors and health outcomes. Recommended broad research themes for funding were health vulnerability, health adaptation, and co-benefits. Other notable recommendations were the development of open data and reproducible modeling schemes. In conclusion, the scoping review was useful in providing a background for research agenda-setting; however, additional analyses or consultations should be complementary for added depth.

Sociodemographic, climatic variability and lower respiratory tract infections: a systematic literature review

Pneumonia is the leading cause of mortality and morbidity in developing countries, particularly for children and elderly. The main objective of this review paper is to review the epidemiological evidence about the effects of sociodemographic and climatic variability on pneumonia and other lower respiratory tract infections. A detailed literature search was conducted in PubMed and Scopus following PRISMA guidelines. The articles, which considered the effect of only climatic or both climatic and sociodemographic factors on pneumonia and other lower respiratory tract infections, included in this review. A total thirty-four relevant articles were reviewed. Of 34 studies, only 14 articles (41%) examined the joint effects of sociodemographic and climate factors on pneumonia and other lower respiratory infections while most of them (59%) assessed climate factors separately. Among these fourteen, only three articles (8.8%) considered detailed sociodemographic factors. All of the reviewed articles suggested different degrees of positive or negative relationship of temperature with pneumonia or other lower respiratory tract infections. Fifteen (44%) articles suggested an association with relative humidity and 13 (38%) with rainfall. Only 3 articles (8.8%) found a relationship with wind speed. Three articles (8.8%) considered other risk factors such as particulate matter 2.5 (PM_2.5) and particulate matter 10 (PM₁₀). One study among the reviewed articles used spatial analysis methods but this study did not examine the joint effects. Among the reviewed articles, 18 (53%) articles used different time series models, one article (3%) used spatiotemporal time series model, 8 (23%) studies used other models and rest 7 (21%) studies used simple descriptive analysis. A total of 18 studies (53%) were conducted in Asia, most of them in China. There were 6 studies (17%) in Europe and 8 studies (23%) in America (South, North and Central). In Africa and Oceania, only one study was found for each region. The joint effect of climate and sociodemographic factors on pneumonia and other lower respiratory tract infections remain to be determined and further research is highly recommended for future prevention of this important and common disease.

Effects of temperature on hospitalisation among pre-school children in Hanoi, Vietnam

This study examined the effect of short-term changes in ambient temperature on hospital admissions among children aged less than 5 years old in Hanoi, Vietnam. Data on daily hospital admissions from January 2010 to June 2014 were collected from two hospitals. Daily meteorological data were obtained for the same period. We applied time series analysis to evaluate the risk of hospitalisation related to hot and cold weather by age and causes. We found that a 1 °C decrease in minimum temperature during the cold weather months was associated with 2.2% increase in hospital admission for respiratory infection among children 3-5 years old. A 1 °C increase in diurnal temperature range (DTR) in cold weather was associated with an increase of 1.9% and 1.7% in hospitalisation for all causes and respiratory infection, respectively, among children < 3 years old and an increase of 1.8% and 3.4% in hospitalisation for all causes and respiratory infection, respectively, among children of 3-5 years old. Negative associations between hot weather and hospital admissions were demonstrated. These findings suggested that low temperature and DTRs in winter are important risk factors for hospital admissions among children aged < 5 years old in Hanoi. Other factors may have modified the effect of high temperature on hospital admissions of children in Hanoi.

Time series modeling of pneumonia admissions and its association with air pollution and climate variables in Chiang Mai Province, Thailand

This study aimed to predict the number of pneumonia cases in Chiang Mai Province. An autoregressive integrated moving average (ARIMA) was used in data fitting and to predict future pneumonia cases monthly. Total pneumonia cases of 67,583 were recorded in Chiang Mai during 2003-2014 that the monthly pattern of case was similar every year. Monthly pneumonia cases were increased during February and September, which are the periods of winter and rainy season in Thailand and decreased during April to July (the period of summer season to early rainy season). Using available data on 12 years of pneumonia cases, air pollution, and climate in Chiang Mai, the optimum ARIMA model was investigated based on several conditions. Seasonal change was included in the models due to statistically strong season conditions. Twelve ARIMA model (ARMODEL1-ARMODEL12) scenarios were investigated. Results showed that the most appropriate model was ARIMA (1,0,2)(2,0,0)[12] with PM10 (ARMODEL5) exhibiting the lowest AIC of - 38.29. The predicted number of monthly pneumonia cases by using ARMODEL5 during January to March 2013 was 727, 707, and 658 cases, while the real number was 804, 868, and 783 cases, respectively. This finding indicated that PM₁₀ held the most important role to predict monthly pneumonia cases in Chiang Mai, and the model was able to predict future pneumonia cases in Chiang Mai accurately.

Firewood, smoke and respiratory diseases in developing countries-The neglected role of outdoor cooking

Smoke from cooking in the kitchen is one of the world’s leading causes of premature child death, claiming the lives of 500,000 children under five annually. This study analyses the role of outdoor cooking and the prevalence of respiratory diseases among children under five years by means of probit regressions using information from 41 surveys conducted in 30 developing countries from Asia, Africa and Latin America. I find that outdoor cooking reduces respiratory diseases among young children aged 0-4 by around 9 percent, an effect that reaches 13 percent among children aged 0-1. The results suggest that simple behavioral interventions, such as promoting outdoor cooking, can have a substantial impact on health hazards.

Risk Prediction for Epithelial Ovarian Cancer in 11 United States-Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci

Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted.

Cooking and season as risk factors for acute lower respiratory infections in African children: a cross-sectional multi-country analysis

Background

Acute lower respiratory infections (ALRI) are a leading cause of death among African children under five. A significant proportion of these are attributable to household air pollution from solid fuel use.

Methods

We assessed the relationship between cooking practices and ALRI in pooled datasets of Demographic and Health Surveys conducted between 2000 and 2011 in countries of sub-Saharan Africa. The impacts of main cooking fuel, cooking location and stove ventilation were examined in 18 (n = 56,437), 9 (n = 23,139) and 6 countries (n = 14,561) respectively. We used a causal diagram and multivariable logistic mixed models to assess the influence of covariates at individual, regional and national levels.

Results

Main cooking fuel had a statistically significant impact on ALRI risk (p<0.0001), with season acting as an effect modifier (p = 0.034). During the rainy season, relative to clean fuels, the odds of suffering from ALRI were raised for kerosene (OR 1.64; CI: 0.99, 2.71), coal and charcoal (OR 1.54; CI: 1.21, 1.97), wood (OR 1.20; CI: 0.95, 1.51) and lower-grade biomass fuels (OR 1.49; CI: 0.93, 2.35). In contrast, during the dry season the corresponding odds were reduced for kerosene (OR 1.23; CI: 0.77, 1.95), coal and charcoal (OR 1.35; CI: 1.06, 1.72) and lower-grade biomass fuels (OR 1.07; CI: 0.69, 1.66) but increased for wood (OR 1.32; CI: 1.04, 1.66). Cooking location also emerged as a season-dependent statistically significant (p = 0.0070) determinant of ALRI, in particular cooking indoors without a separate kitchen during the rainy season (OR 1.80; CI: 1.30, 2.50). Due to infrequent use in Africa we could, however, not demonstrate an effect of stove ventilation.

Conclusions

We found differential and season-dependent risks for different types of solid fuels and kerosene as well as cooking location on child ALRI. Future household air pollution studies should consider potential effect modification of cooking fuel by season.

Clinical risk factors for life-threatening lower respiratory tract infections in children: a retrospective study in an urban city in Malaysia

AIM

Lower respiratory tract infections (LRTIs) are an important cause of morbidity and mortality, especially in low income countries. The aim of this study was to determine risk factors of life-threatening LRTIs in hospitalised children in Malaysia.

METHODS

This retrospective study included children aged less than 18 years admitted for LRTIs over 13 months in a tertiary referral centre in Kuala Lumpur, Malaysia. Neonates, children with asthma and those with either no or a normal chest radiograph were excluded. Life-threatening infection was defined as that needing non-invasive ventilation or admission to the paediatric intensive care unit. Routine blood investigations and nasopharyngeal secretion results (bacterial and viral) were obtained. Chest radiographs were reviewed by a designated radiologist. Environmental data (rainfall, particulate matter ≤ 10 µm [PM10] and air pollution index [API]) was obtained from the respective government departments.

RESULTS

Three hundred and ninety-one episodes of LRTIs were included. Viruses were implicated in 48.5% of LRTIs, with respiratory syncytial virus (RSV) being detected in 44% of viral LRTIs. Forty-six (11.8%) children had life-threatening disease and the overall mortality rate was 1.3% (5 children). RSV was detected in 26% of children with life-threatening LRTIs. In multivariate logistic regression, chronic lung disease, presenting history of apnoea and signs of hypoxia, was associated with life threatening LRTIs. Increased LRTI admissions were associated with low rainfall but not PM10 nor API. Of those on follow-up, 39% had persistent respiratory symptoms.

CONCLUSION

One in nine children admitted with LRTI had a life-threatening LRTI. The aetiology was viral in almost half of admitted children. RSV was detected in a quarter of children with life-threatening LRTIs. Children who present with LRTIs and either have chronic lung disease, presenting history of apnoea or signs of hypoxia, should be observed carefully as the risk of deterioration to life-threatening illness is high.

The geographical co-distribution and socio-ecological drivers of childhood pneumonia and diarrhoea in Queensland, Australia

SUMMARY This study aimed to explore the spatio-temporal patterns, geographical co-distribution, and socio-ecological drivers of childhood pneumonia and diarrhoea in Queensland. A Bayesian conditional autoregressive model was used to quantify the impacts of socio-ecological factors on both childhood pneumonia and diarrhoea at a postal area level. A distinct seasonality of childhood pneumonia and diarrhoea was found. Childhood pneumonia and diarrhoea were mainly distributed in the northwest of Queensland. Mount Isa city was the high-risk cluster where childhood pneumonia and diarrhoea co-distributed. Emergency department visits (EDVs) for pneumonia increased by 3% per 10-mm increase in monthly average rainfall in wet seasons. By comparison, a 10-mm increase in monthly average rainfall may cause an increase of 4% in EDVs for diarrhoea. Monthly average temperature was negatively associated with EDVs for childhood diarrhoea in wet seasons. Low socioeconomic index for areas (SEIFA) was associated with high EDVs for childhood pneumonia. Future pneumonia and diarrhoea prevention and control measures in Queensland should focus more on Mount Isa.

Impact of temperature on childhood pneumonia estimated from satellite remote sensing

The effect of temperature on childhood pneumonia in subtropical regions is largely unknown so far. This study examined the impact of temperature on childhood pneumonia in Brisbane, Australia. A quasi-Poisson generalized linear model combined with a distributed lag non-linear model was used to quantify the main effect of temperature on emergency department visits (EDVs) for childhood pneumonia in Brisbane from 2001 to 2010. The model residuals were checked to identify added effects due to heat waves or cold spells. Both high and low temperatures were associated with an increase in EDVs for childhood pneumonia. Children aged 2-5 years, and female children were particularly vulnerable to the impacts of heat and cold, and Indigenous children were sensitive to heat. Heat waves and cold spells had significant added effects on childhood pneumonia, and the magnitude of these effects increased with intensity and duration. There were changes over time in both the main and added effects of temperature on childhood pneumonia. Children, especially those female and Indigenous, should be particularly protected from extreme temperatures. Future development of early warning systems should take the change over time in the impact of temperature on children's health into account.

Temperature variability and childhood pneumonia: an ecological study

BACKGROUND

Few data on the relationship between temperature variability and childhood pneumonia are available. This study attempted to fill this knowledge gap.

METHODS

A quasi-Poisson generalized linear regression model combined with a distributed lag non-linear model was used to quantify the impacts of diurnal temperature range (DTR) and temperature change between two neighbouring days (TCN) on emergency department visits (EDVs) for childhood pneumonia in Brisbane, from 2001 to 2010, after controlling for possible confounders.

RESULTS

An adverse impact of TCN on EDVs for childhood pneumonia was observed, and the magnitude of this impact increased from the first five years (2001-2005) to the second five years (2006-2010). Children aged 5-14 years, female children and Indigenous children were particularly vulnerable to TCN impact. However, there was no significant association between DTR and EDVs for childhood pneumonia.

CONCLUSIONS

As climate change progresses, the days with unstable weather pattern are likely to increase. Parents and caregivers of children should be aware of the high risk of pneumonia posed by big TCN and take precautionary measures to protect children, especially those with a history of respiratory diseases, from climate impacts.

Using mathematical transmission modelling to investigate drivers of respiratory syncytial virus seasonality in children in the Philippines

We used a mathematical transmission model to estimate when ecological drivers of respiratory syncytial virus (RSV) transmissibility would need to act in order to produce the observed seasonality of RSV in the Philippines. We estimated that a seasonal peak in transmissibility would need to occur approximately 51 days prior to the observed peak in RSV cases (range 49 to 67 days). We then compared this estimated seasonal pattern of transmissibility to the seasonal patterns of possible ecological drivers of transmissibility: rainfall, humidity and temperature patterns, nutritional status, and school holidays. The timing of the seasonal patterns of nutritional status and rainfall were both consistent with the estimated seasonal pattern of transmissibility and these are both plausible drivers of the seasonality of RSV in this setting.

Poor growth and pneumonia seasonality in infants in the Philippines: cohort and time series studies

Children with poor nutrition are at increased risk of pneumonia. In many tropical settings seasonal pneumonia epidemics occur during the rainy season, which is often a period of poor nutrition. We have investigated whether seasonal hunger may be a driver of seasonal pneumonia epidemics in children in the tropical setting of the Philippines. In individual level cohort analysis, infant size and growth were both associated with increased pneumonia admissions, consistent with findings from previous studies. A low weight for age z-score in early infancy was associated with an increased risk of pneumonia admission over the following 12 months (RR for infants in the lowest quartile of weight for age z-scores 1.28 [95% CI 1.08 to 1.51]). Poor growth in smaller than average infants was also associated with an increased risk of pneumonia (RR for those in the lowest quartile of growth in early infancy 1.31 [95%CI 1.02 to 1.68]). At a population level, we found that seasonal undernutrition preceded the seasonal increase in pneumonia and respiratory syncytial virus admissions by approximately 10 weeks (pairwise correlation at this lag was −0.41 [95%CI −0.53 to −0.27] for pneumonia admissions, and −0.63 [95%CI −0.72 to −0.51] for respiratory syncytial virus admissions). This lag appears biologically plausible. These results suggest that in addition to being an individual level risk factor for pneumonia, poor nutrition may act as a population level driver of seasonal pneumonia epidemics in the tropics. Further investigation of the seasonal level association, in particular the estimation of the expected lag between seasonal undernutrition and increased pneumonia incidence, is recommended.

Influenza and RSV make a modest contribution to invasive pneumococcal disease incidence in the UK

Objectives

The common seasonality of incidence of invasive pneumococcal disease (IPD) and viral respiratory infections has long been recognized, however, the extent to which this affects the association between the pathogens is unknown. We have analysed weekly surveillance data of IPD, influenza and respiratory syncytial virus (RSV), using ambient temperature and hours of sunshine as measures of seasonality.

Methods

Reported cases of influenza, IPD and RSV, were collected in England and Wales, from week 1 (January) 1996 to week 23 (June) 2009. The associations between IPD and respiratory viral infections were analysed using several statistical methods, including correlation coefficients and both additive and multiplicative regression models.

Results

6–7.5% of cases of IPD are attributable to influenza and 3–4% attributable to RSV. Correlation coefficients reported considerably stronger associations between IPD and the viral infections compared to regression models.

Conclusions

A small but potentially important percentage of IPD may be attributable to influenza and RSV when adjusted for seasonality by temperature. Jointly these viral infections may lead to over 10% of IPD cases. Therefore, prevention of viral respiratory infections may offer some additional benefit in reducing invasive pneumococcal infections.