Seasonal variation and etiologic inferences of childhood pneumonia and diarrhea mortality in India

Two Decades of Melioidosis in India: A Comprehensive Epidemiological Review

Melioidosis, caused by Burkholderia pseudomallei, is a potentially fatal infection, particularly affecting individuals with chronic conditions such as diabetes or kidney or liver diseases. This review examines melioidosis in India over the past two decades, focusing on its prevalence, risk factors and clinical manifestations. A PubMed search (2000-2024) identified a rise in melioidosis publications, with most from Southern India, followed by Eastern India, and an increase post-2019. Eight studies from 2010-2022 identified fever (86%), cough (26%) and joint pain (23%) as the most common symptoms, while diabetes (75%), alcohol abuse (19%) and cancer (6%) were primary predisposing factors. Severe clinical manifestations were also observed, including bacteremia (50%), pneumonia (37%) and splenic abscess (18%). Although environmental exposure risks were not significantly high, individuals with diabetes or chronic kidney disease, particularly those working in high-risk environments, were more likely to contract melioidosis. Cryptic environmental factors that might bridge known epidemiological risk factors are also addressed. The review emphasizes the increasing awareness and research in clinical epidemiology and also highlights a gap in studies on antimicrobial treatments, vaccines and environmental surveillance. Targeted interventions in diabetes and poverty hotspots could help control the disease more effectively.

Differential Effectiveness of Water, Sanitation, and Handwashing Interventions to Reduce Child Diarrhea in Dry and Rainy Seasons: A Systematic Review and Meta-Analysis of Intervention Trials

BACKGROUND

Studies evaluating how water, sanitation, and/or handwashing (WASH) interventions in low- and middle-income countries impact diarrheal diseases have shown inconsistent results. The prevalence of enteric pathogen infections and diarrhea are highly seasonal and climate-sensitive, which could explain heterogeneous findings. Understanding how season influences the effectiveness of WASH interventions is critical for informing intervention approaches that will be resistant under the varying weather conditions that climate change will bring.

METHODS

We conducted a systematic review of the literature and meta-analysis to test whether and to what extent the impact of WASH interventions on diarrhea differs by season. We searched the literature for randomized and nonrandomized controlled WASH intervention trials and identified the season in which data were collected-rainy, dry, or both-for each study using proximate land station weather datasets. We compared the relative risk (RR) estimates for the impact of interventions on diarrhea for each study, stratified by season, and analyzed estimates using meta-analysis and meta-regression. This study is registered with PROSPERO, CRD42021231137.

RESULTS

A total of 50 studies met the inclusion criteria, resulting in 34 drinking water intervention estimates, 8 sanitation intervention estimates, and 14 handwashing intervention estimates. Of the total studies, 60% (n = 30 ) spanned more than one season, with most single-season studies (75%, n = 15 ) occurring exclusively in the dry season. The effect of WASH interventions was stronger in dry seasons than in rainy seasons, with a 33% [95% confidence interval (CI): 24%, 41%] and 18% reduction (95% CI: 5%, 29%) in diarrhea risk, respectively. When stratified by type of intervention, the stronger effect size in dry seasons was consistent for water and handwashing interventions but not for sanitation interventions.

CONCLUSIONS

Estimates of the seasonal impact of WASH interventions revealed larger effects in the dry season than in the rainy season overall and for water and handwashing interventions in particular. These patterns likely affected previous estimates of intervention effectiveness, which included more dry season estimates. These findings suggest the need to collect data across seasons and report seasonally stratified results to allow for more accurate estimates of the burden of disease impacted by WASH investments and to improve projections of potential impacts of these interventions under future climate conditions. These findings also underscore the need for robust WASH interventions designed to be resistant to seasonal variations in temperature and rainfall now and under future climate change scenarios. https://doi.org/10.1289/EHP14502.

Association between precipitation and mortality due to diarrheal diseases by climate zone: A multi-country modeling study

Background

Precipitation could affect the transmission of diarrheal diseases. The diverse precipitation patterns across different climates might influence the degree of diarrheal risk from precipitation. This study determined the associations between precipitation and diarrheal mortality in tropical, temperate, and arid climate regions.

Methods

Daily counts of diarrheal mortality and 28-day cumulative precipitation from 1997 to 2019 were analyzed across 29 locations in eight middle-income countries (Argentina, Brazil, Costa Rica, India, Peru, the Philippines, South Africa, and Thailand). A two-stage approach was employed: the first stage is conditional Poisson regression models for each location, and the second stage is meta-analysis for pooling location-specific coefficients by climate zone.

Results

In tropical climates, higher precipitation increases the risk of diarrheal mortality. Under extremely wet conditions (95th percentile of 28-day cumulative precipitation), diarrheal mortality increased by 17.8% (95% confidence interval [CI] = 10.4%, 25.7%) compared with minimum-risk precipitation. For temperate and arid climates, diarrheal mortality increases in both dry and wet conditions. In extremely dry conditions (fifth percentile of 28-day cumulative precipitation), diarrheal mortality risk increases by 3.8% (95% CI = 1.2%, 6.5%) for temperate and 5.5% (95% CI = 1.0%, 10.2%) for arid climates. Similarly, under extremely wet conditions, diarrheal mortality risk increases by 2.5% (95% CI = -0.1%, 5.1%) for temperate and 4.1% (95% CI = 1.1%, 7.3%) for arid climates.

Conclusions

Associations between precipitation and diarrheal mortality exhibit variations across different climate zones. It is crucial to consider climate-specific variations when generating global projections of future precipitation-related diarrheal mortality.

Implementing Community-Based Strategies for Improved Pneumonia Care in Children: Insights From a Pilot Study

INTRODUCTION

Respiratory ailments, encompassing a spectrum of disorders, are a leading cause of mortality and morbidity in children, with pneumonia being particularly significant, accounting for 16% of child mortality. To ensure timely engagement with healthcare services, it is imperative to instill awareness through Information, Education, and Communication (IEC) initiatives targeting mothers of children under five. The primary objective of this pilot study is to assess the feasibility of a community-based intervention on health-seeking behaviour, knowledge, and practice measures concerning the management and prevention of pneumonia in children.

METHODOLOGY

The pilot study mirrored the main study's procedures in two villages, Bhuvanahalli and Gavanahalli, each randomly assigned as either an experimental or a control group. We selected 12 mothers with children under the age of five who had community-acquired pneumonia, employing a straightforward random technique, with six mothers from each group. These mothers were interviewed using a structured questionnaire focusing on health-seeking behaviour, knowledge, and practices related to the management and prevention of pneumonia. Mothers in the experimental group received a community-based intervention, specifically an educational set focusing on health-seeking behaviour, knowledge, and practice measures concerning the management and prevention of pneumonia in children, while those in the control group continued with their routine practices. We collected post-test data from the mothers in both groups at the 2nd, 4th, and 6th months of the intervention. The data analysis was conducted using the IBM SPSS Statistics for Windows, Version 28 (Released 2021; IBM Corp., Armonk, New York) software. The Mann-Whitney test and Kruskal-Wallis analyses indicated a notable and statistically significant shift in health-seeking behaviour, knowledge, and practices pertaining to the management and prevention of pneumonia in children as a result of the community-based educational intervention implemented in the experimental group (P<0.05).

CONCLUSION

Community-based intervention is crucial to preventing mortality and morbidity in children. The findings of the pilot study affirm its feasibility and lay a strong foundation for further investigation and implementation.

Childhood Pneumonia in Low- and Middle-Income Countries: A Systematic Review of Prevalence, Risk Factors, and Healthcare-Seeking Behaviors

Childhood pneumonia is a major contributor to illness and death in children under the age of five globally. Despite advancements in medical science, the burden of pediatric community-acquired pneumonia (CAP) remains high, particularly in low- and middle-income countries. This systematic review aims to synthesize existing literature on the prevalence, risk factors, and healthcare-seeking behaviors associated with pediatric CAP to inform the development of targeted community-based interventions. An extensive search of various databases such as Medline, EMBASE, Web of Science, Cochrane, PubMed, PubMed Central, Helinet, SpringerLink, Google Scholar, and Biomed Central was performed, resulting in 65 potentially relevant studies. After a thorough evaluation process, 25 studies were selected for the final analysis. These selected studies offered valuable information on the epidemiology, risk factors, and healthcare-seeking behaviors associated with childhood pneumonia. The review revealed that environmental factors such as indoor air pollution, overcrowding, and exposure to tobacco smoke are significant risk factors for pediatric pneumonia. Additionally, socioeconomic factors, including poverty and a lack of access to clean water and sanitation, contribute to the vulnerability of children to this disease. Poor healthcare-seeking behaviors, driven by limited knowledge and awareness of pneumonia symptoms and treatment, further exacerbate the situation. The review also highlighted the critical role of vaccination, particularly against Haemophilus influenzae type b (Hib) and pneumococcus, in preventing pneumonia. However, gaps in vaccination coverage and challenges in accessing healthcare services remain barriers to effective pneumonia control. In light of these findings, the review recommends the implementation of community-based interventions that address the multifaceted determinants of pediatric pneumonia. These interventions should focus on improving environmental conditions, enhancing access to preventive measures such as vaccination, and promoting better healthcare-seeking behaviors through education and awareness campaigns. It is essential for healthcare providers, policymakers, and community members to collaborate in developing and implementing culturally appropriate and sustainable interventions. This cooperation aims to lessen the impact of pneumonia on children and their families.

Meteorological Factors Affecting Infectious Diarrhea in Different Climate Zones of China

Meteorological factors and the increase in extreme weather events are closely related to the incidence rate of infectious diarrhea. However, few studies have explored whether the impact of the same meteorological factors on the incidence rate of infectious diarrhea in different climate regions has changed and quantified these changes. In this study, the time series fixed-effect Poisson regression model guided by climate was used to quantify the relationships between the incidence rate of various types of infectious diarrhea and meteorological factors in different climate regions of China from 2004 to 2018, with a lag of 0-2 months. In addition, six social factors, including per capita Gross Domestic Product (GDP), population density, number of doctors per 1000 people, proportion of urbanized population, proportion of children aged 0-14 years old, and proportion of elderly over 65 years old, were included in the model for confounding control. Additionally, the intercept of each province in each model was analyzed by a meta-analysis. Four climate regions were considered in this study: tropical monsoon areas, subtropical monsoon areas, temperate areas and alpine plateau areas. The results indicate that the influence of meteorological factors and extreme weather in different climate regions on diverse infectious diarrhea types is distinct. In general, temperature was positively correlated with all infectious diarrhea cases (0.2 ≤ r ≤ 0.6, p < 0.05). After extreme rainfall, the incidence rate of dysentery in alpine plateau area in one month would be reduced by 18.7% (95% confidence interval (CI): -27.8--9.6%). Two months after the period of extreme sunshine duration happened, the incidence of dysentery in the alpine plateau area would increase by 21.9% (95% CI: 15.4-28.4%) in that month, and the incidence rate of typhoid and paratyphoid in the temperate region would increase by 17.2% (95% CI: 15.5-18.9%) in that month. The meta-analysis showed that there is no consistency between different provinces in the same climate region. Our study indicated that meteorological factors and extreme weather in different climate areas had different effects on various types of infectious diarrhea, particularly extreme rainfall and extreme sunshine duration, which will help the government develop disease-specific and location-specific interventions, especially after the occurrence of extreme weather.

Causes of infant deaths and patterns of associated factors in Eastern Ethiopia: Results of verbal autopsy (InterVA-4) study

Background

In a range of setting, detecting and generate empirical information on the cause of infant death and contributing risk factors at population level is basically utmost essential to take evidence-based measures in reducing infant morbidity and mortality. An electronic verbal autopsy is suitable tool and best alternative solution to determine individuals’ cause of death in a setting where the majority of deaths occur at home and civil registration systems do not exist. The present study was undertaken to find out cause of infant death, applying computer-based probabilistic model (InterVA-4) and analyze the patterns of association factors of mother’s and the deceased infant’s characteristics to the leading cause-specific infant mortality in Eastern Ethiopia.

Methods

The study employed a community-based prospective longitudinal survey, which was conducted with routinely enumeration of reported infant deaths for a period of two years (from September 2016 to August 2018) in Eastern part of Ethiopia. Using the two-stage cluster sampling technique, the study was undertaken in four randomly selected districts of West Hararghe zone and two districts of zone 3 in Oromia and Afar regional state, respectively. The study included a total of 362 infants who were deceased during the study period. Data was collected by trained enumerators by interviewing the mothers or guardians of the deceased infant using a 2014 standardize World Health Organization (WHO) Verbal Autopsy questionnaire. InterVA-4 model were used for processing and interpreting verbal autopsy data in order to arrive at the most likely causes of infant death. SPSS version 23 was also used for statistical analysis of frequency distribution and logistic regression for the association between covariates and outcomes.

Findings

Of the overall (362) deceased infants’ during the study period, 53.0% of deaths occurred during neonatal time while 47.0% died in the post-neonatal period. Acute respiratory infection including neonatal and post-neonatal pneumonia (38.4%), birth asphyxia (16.4%), diarrheal diseases (16.3%), prematurity (7.4%) and malaria (4.3%) were found to be the leading causes of infant mortality in the study area. The independent factors strongly associated with probable ARI, including pneumonia related mortality as compared to all-causes of death were infants with maternal age lower than 20 years old (p = 0.001, AOR: 4.82, 95% CI: 1.88, 12.3) and infant being died outside of heath facilities (P = 0.007, AOR: 2.85, 95% CI: 1.33, 6.12). The post-neonatal period (P = 0.000, AOR: 15.5, 95% CI: 6.35, 37.8) and infant died in the wet season (P = 0.006, AOR: 2.38, 95% CI: 1.28, 4.44) had strong relationship with dying from diarrhea-related death than those infants died from all non-diarrhea. The death due to malaria robustly associated with infants whose mothers age between 20–35 years old (P = 0.024, AOR: 4.44, 95% CI: 1.22, 16.2) and infant who was dwelled in the districts of Afar region (P = 0.013, AOR: 4.08, 95% CI: 1.35, 12.4).

Conclusion

The highest cause of infant mortality was associated with disease of respiratory system, particularly acute respiratory infection, including both neonates and post-neonatal pneumonia. Most of the infant deaths existed are as a result of diseases and conditions that are readily preventable or treatable cause, similar to those reported in worldwide, which have needs of further attention. The patterns of significant associated factors across cause-specific mortality against all-cause of death were dissimilar. Therefore, strengthen maternal and child health program with effective preventive interventions emphasizing on the most common cause of infant deaths and those factors contributing in raising mortality risk are required.

Projecting Temperature-Attributable Mortality and Hospital Admissions due to Enteric Infections in the Philippines

BACKGROUND

Enteric infections cause significant deaths, and global projection studies suggest that mortality from enteric infections will increase in the future with warmer climate. However, a major limitation of these projection studies is the use of risk estimates derived from nonmortality data to project excess enteric infection mortality associated with temperature because of the lack of studies that used actual deaths.

OBJECTIVE

We quantified the associations of daily temperature with both mortality and hospital admissions due to enteric infections in the Philippines. These associations were applied to projections under various climate and population change scenarios.

METHODS

We modeled nonlinear temperature associations of mortality and hospital admissions due to enteric infections in 17 administrative regions of the Philippines using a two-stage time-series approach. First, we quantified nonlinear temperature associations of enteric infections by fitting generalized linear models with distributed lag nonlinear models. Second, we combined regional estimates using a meta-regression model. We projected the excess future enteric infections due to nonoptimal temperatures using regional temperature-enteric infection associations under various combinations of climate change scenarios according to representative concentration pathways (RCPs) and population change scenarios according to shared socioeconomic pathways (SSPs) for 2010-2099.

RESULTS

Regional estimates for mortality and hospital admissions were significantly heterogeneous and had varying shapes in association with temperature. Generally, mortality risks were greater in high temperatures, whereas hospital admission risks were greater in low temperatures. Temperature-attributable excess deaths in 2090-2099 were projected to increase over 2010-2019 by as little as 1.3% [95% empirical confidence intervals (eCI): -3.1%, 6.5%] under a low greenhouse gas emission scenario (RCP 2.6) or as much as 25.5% (95% eCI: -3.5%, 48.2%) under a high greenhouse gas emission scenario (RCP 8.5). A moderate increase was projected for temperature-attributable excess hospital admissions, from 0.02% (95% eCI: -2.0%, 1.9%) under RCP 2.6 to 5.2% (95% eCI: -12.7%, 21.8%) under RCP 8.5 in the same period. High temperature-attributable deaths and hospital admissions due to enteric infections may occur under scenarios with high population growth in 2090-2099.

DISCUSSION

In the Philippines, futures with hotter temperatures and high population growth may lead to a greater increase in temperature-related excess deaths than hospital admissions due to enteric infections. Our results highlight the need to strengthen existing primary health care interventions for diarrhea and support health adaptation policies to help reduce future enteric infections. https://doi.org/10.1289/EHP9324.

What are the determinants of childhood infections in India's peri-urban slums? A case study of eight cities

BACKGROUND

Respiratory Tract Infections (RTIs) and Gastro-Intestinal (GI) infections are the leading causes of child mortality and morbidity. This study investigates the associations between the individual, household and slum-level determinants of children's health and vulnerability to RTIs and GI infections in peri-urban slums in India; an area of research interest at the Childhood Infections and Pollution Consortium.

METHODS

The 2015-16 Indian National Family Health Survey was used for data analysis on children aged 0-5 years. NFHS-4 includes data on slums in eight Indian cities, including Delhi, Meerut, Kolkata, Indore, Mumbai, Nagpur, Hyderabad, Chennai. The outcome variables, having fever and cough (FeCo) and diarrhoea in the last two weeks, were used to define the phenotype of infections; for this analysis fever and cough were measures of RTIs and diarrhoea was used to measure GI infections. Exposures considered in this study include variables at the individual, household and slum level and were all informed by existing literature. Multilevel models were used to estimate the association between exposures and outcomes variables; a prior of Cauchy distribution with a scale of 2.5 was selected when building the multilevel logistic models.

RESULTS

The total sample size of the number of children included in the analysis was n = 1,424. Data was imputed to account for missingness, and the original and imputed sample showing similar distributions. Results showed that diarrhoea and FeCo were both found to be more present in younger children than older children by a few months. In fixed effects, the odds of developing FeCo were higher if the mother perceives the child was born smaller than average (AOR 4.41, 1.13-17.17, P<0.05) at individual level. On the other hand, the odds of the diarrhoea outcome were lower if the child was older (AOR 0.97, 0.96-0.98, P<0.05) at individual level, and household's water source was public tap or standpipe (AOR 0.54, 0.31-0.96, P<0.05) at household level.

CONCLUSION

The determinants of health, both social and related to health care, at all levels demonstrated linkages to child morbidity in RTIs and GI infections. The empirical evidence highlights the need for contextualised ideas at each level, including one health approach when designing interventions to improve 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.

A modular approach to integrating multiple data sources into real-time clinical prediction for pediatric diarrhea

Traditional clinical prediction models focus on parameters of the individual patient. For infectious diseases, sources external to the patient, including characteristics of prior patients and seasonal factors, may improve predictive performance. We describe the development of a predictive model that integrates multiple sources of data in a principled statistical framework using a post-test odds formulation. Our method enables electronic real-time updating and flexibility, such that components can be included or excluded according to data availability. We apply this method to the prediction of etiology of pediatric diarrhea, where 'pre-test’ epidemiologic data may be highly informative. Diarrhea has a high burden in low-resource settings, and antibiotics are often over-prescribed. We demonstrate that our integrative method outperforms traditional prediction in accurately identifying cases with a viral etiology, and show that its clinical application, especially when used with an additional diagnostic test, could result in a 61% reduction in inappropriately prescribed antibiotics.