Evaluating meteorological data from weather stations, and from satellites and global models for a multi-site epidemiological study.

BACKGROUND: Longitudinal and time series analyses are needed to characterize the associations between hydrometeorological parameters and health outcomes. Earth Observation (EO) climate data products derived from satellites and global model-based reanalysis have the potential to be used as surrogates in situations and locations where weather-station based observations are inadequate or incomplete. However, these products often lack direct evaluation at specific sites of epidemiological interest. METHODS: Standard evaluation metrics of correlation, agreement, bias and error were applied to a set of ten hydrometeorological variables extracted from two quasi-global, commonly used climate data products - the Global Land Data Assimilation System (GLDAS) and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) - to evaluate their performance relative to weather-station derived estimates at the specific geographic locations of the eight sites in a multi-site cohort study. These metrics were calculated for both daily estimates and 7-day averages and for a rotavirus-peak-season subset. Then the variables from the two sources were each used as predictors in longitudinal regression models to test their association with rotavirus infection in the cohort after adjusting for covariates. RESULTS: The availability and completeness of station-based validation data varied depending on the variable and study site. The performance of the two gridded climate models varied considerably within the same location and for the same variable across locations, according to different evaluation criteria and for the peak-season compared to the full dataset in ways that showed no obvious pattern. They also differed in the statistical significance of their association with the rotavirus outcome. For some variables, the station-based records showed a strong association while the EO-derived estimates showed none, while for others, the opposite was true. CONCLUSION: Researchers wishing to utilize publicly available climate data - whether EO-derived or station based - are advised to recognize their specific limitations both in the analysis and the interpretation of the results. Epidemiologists engaged in prospective research into environmentally driven diseases should install their own weather monitoring stations at their study sites whenever possible, in order to circumvent the constraints of choosing between distant or incomplete station data or unverified EO estimates.

Bhaktapur, Nepal: the MAL-ED birth cohort study in Nepal.

The Etiology, Risk Factors and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health and Development (MAL-ED) cohort study site in Nepal is located in the Bhaktapur municipality, 15 km east of Kathmandu, the capital city of Nepal. Bhaktapur, an ancient city famous for its traditional temples and buildings, is included on UNESCO's World Heritage List and is a major tourist attraction in Nepal. Nepal is a land-locked country located in South Asia between China and India with an area of 147 181 km(2), ranging from sea-level plains to Mount Everest, the world's highest peak. The total population as of the 2011 census was 26.6 million, with an average annual population growth rate of 1.4. Nepal is one of the world's least developed countries and is ranked 157 of 186 in the 2013 Human Development Report; one-third of the Nepali population lives below the poverty line. The current under-5 mortality rate is 54 per 1000 live births, the infant mortality rate is 46 per 1000 live births, and the neonatal mortality rate is 33 per 1000 live births. Vaccine coverage for all Expanded Program on Immunization vaccines is >80%. Among children, the most common diseases contributing to significant morbidity and mortality are acute respiratory infection and dehydration from severe diarrhea. In this article, we report on the geographic, demographic, and socioeconomic features of the Bhaktapur MAL-ED site and describe the data that informed our cohort recruitment strategy.

Associations Between Eight Earth Observation-Derived Climate Variables and Enteropathogen Infection: An Independent Participant Data Meta-Analysis of Surveillance Studies With Broad Spectrum Nucleic Acid Diagnostics.

Diarrheal disease, still a major cause of childhood illness, is caused by numerous, diverse infectious microorganisms, which are differentially sensitive to environmental conditions. Enteropathogen-specific impacts of climate remain underexplored. Results from 15 studies that diagnosed enteropathogens in 64,788 stool samples from 20,760 children in 19 countries were combined. Infection status for 10 common enteropathogens-adenovirus, astrovirus, norovirus, rotavirus, sapovirus, Campylobacter, ETEC, Shigella, Cryptosporidium and Giardia-was matched by date with hydrometeorological variables from a global Earth observation dataset-precipitation and runoff volume, humidity, soil moisture, solar radiation, air pressure, temperature, and wind speed. Models were fitted for each pathogen, accounting for lags, nonlinearity, confounders, and threshold effects. Different variables showed complex, non-linear associations with infection risk varying in magnitude and direction depending on pathogen species. Rotavirus infection decreased markedly following increasing 7-day average temperatures-a relative risk of 0.76 (95% confidence interval: 0.69-0.85) above 28°C-while ETEC risk increased by almost half, 1.43 (1.36-1.50), in the 20-35°C range. Risk for all pathogens was highest following soil moistures in the upper range. Humidity was associated with increases in bacterial infections and decreases in most viral infections. Several virus species' risk increased following lower-than-average rainfall, while rotavirus and ETEC increased with heavier runoff. Temperature, soil moisture, and humidity are particularly influential parameters across all enteropathogens, likely impacting pathogen survival outside the host. Precipitation and runoff have divergent associations with different enteric viruses. These effects may engender shifts in the relative burden of diarrhea-causing agents as the global climate changes.

Predictors of duration and treatment failure of severe pneumonia in hospitalized young Nepalese children.

BACKGROUND: Pneumonia in young children is still the most frequent cause of death in developing countries. We aimed to identify predictors for recovery and treatment failure in children hospitalized with severe pneumonia. METHODS: We enrolled 610 Nepalese children, aged 2 - 35 months from February 2006 to June 2008. Study participants were provided with standard treatment for pneumonia and followed up until discharge. Three multiple regression models representing clinical variables, clinical and radiological combined and all variables, including C-reactive protein (CRP) and viral etiology were used to assess the associations. RESULTS: The median age of study participants was 6 months with 493 (82%) infants and 367 (61%) males. The median time (IQR) till recovery was 49 (31, 87) hours and treatment failure was experienced by 209 (35%) of the children. Younger age, hypoxia on admission and radiographic pneumonia were independent predictors for both prolonged recovery and risk of treatment failure. While wasting and presence of any danger sign also predicted slower recovery, Parainfluenza type 1 isolated from the nasopharynx was associated with earlier resolution of illness. Gender, being breastfed, stunting, high fever, elevated CRP, presence of other viruses and supplementation with oral zinc did not show any significant association with these outcomes. CONCLUSION: Age, hypoxia and consolidation on chest radiograph were significant predictors for time till recovery and treatment failure in children with severe pneumonia. While chest radiograph is not always needed, detection and treatment of hypoxia is a crucial step to guide the management of hospitalized children with pneumonia.