nasa-gesdisc/es-publications-researchareas huggingface dataset:
Global mapping of highly pathogenic avian influenza H5N1 and H5Nx clade 2.3.4.4 viruses with spatial cross-validation (2016)

Global disease suitability models are essential tools to inform surveillance systems and enable early detection. We present the first global suitability model of highly pathogenic avian influenza (HPAI) H5N1 and demonstrate that reliable predictions can be obtained at global scale. Best predictions are obtained using spatial predictor variables describing host distributions, rather than land use or eco-climatic spatial predictor variables, with a strong association with domestic duck and extensively raised chicken densities. Our results also support a more systematic use of spatial cross-validation in large-scale disease suitability modelling compared to standard random cross-validation that can lead to unreliable measure of extrapolation accuracy. A global suitability model of the H5 clade 2.3.4.4 viruses, a group of viruses that recently spread extensively in Asia and the US, shows in comparison a lower spatial extrapolation capacity than the HPAI H5N1 models, with a stronger association with intensively raised chicken densities and anthropogenic factors.

Research areas: Public Health
Identification of factors associated with residual malaria transmission (2022)

Abstract
            
              Background
              
                Targeted research on residual malaria transmission is important to improve strategies in settings pursuing elimination, where transmission reductions prove challenging. This study aimed to detect and characterize spatial heterogeneity and factors associated with
                Plasmodium falciparum
                infections and exposure,
                P. falciparum
                apical membrane antigen 1 (PfAMA1) antibody (Ab) response, in the Central Highlands of Madagascar (CHL).
              
            
            
              Methods
              
                From May to July 2014, a cross-sectional school-based survey was carried out in 182
                fokontany
                (villages) within 7 health districts of the CHL. Rapid diagnostic tests (RDTs) and a bead-based immunoassay including PfAMA1 antigen biomarker were used to estimate malaria prevalence and seroprevalence, respectively. Local Morans I index was used to detect spatial hotspots. Remotely sensed environmental datatemperature, vegetation indices, land covers, and elevationwere used in multivariable mixed-effects logistic regression models to characterize factors associated with malaria infection and cumulative exposure.
              
            
            
              Results
              Among 6,293 school-children ages 214 years surveyed, RDT prevalence was low at 0.8% (95% CI 0.61.1%), while PfAMA1 Ab seroprevalence was 7.0% (95% CI 6.47.7%). Hotspots of PfAMA1 Ab seroprevalence were observed in two districts (Ankazobe and Mandoto). Seroprevalence increased for children living > 5 km from a health centre (adjusted odds ratio (OR) = 1.6, 95% CI 1.22.2), and for those experiencing a fever episode in the previous 2 weeks (OR 1.7, 95% CI 1.22.4), but decreased at higher elevation (for each 100-m increase, OR = 0.7, 95% CI 0.60.8). A clear age pattern was observed whereby children 910 years old had an OR of 1.8 (95% CI 1.22.4), children 1112 years an OR of 3.7 (95% CI 2.85.0), and children 1314 years an OR of 5.7 (95% CI 4.08.0) for seropositivity, compared with younger children (28 years).
            
            
              Conclusion
              The use of serology in this study provided a better understanding of malaria hotspots and associated factors, revealing a pattern of higher transmission linked to geographical barriers in health care access. The integration of antibody-assays into existing surveillance activities could improve exposure assessment, and may help to monitor the effectiveness of malaria control efforts and adapt elimination interventions.

Research areas: Public Health
Comparison of temperature-mortality associations estimated with different exposure metrics (2019)

 Background: Studies of the short-term association between ambient temperature and mortality often use temperature observations from a single monitoring station, frequently located at the nearest airport, to represent the exposure of individuals living across large areas. Population-weighted temperature estimates constructed from gridded meteorological data may offer an opportunity to improve exposure assessment in locations where station observations do not fully capture the average exposure of the population of interest. Methods: We compared the association between daily mean temperature and mortality in each of 113 United States counties using (1) temperature observations from a single weather station and (2) population-weighted temperature estimates constructed from a gridded meteorological dataset. We used distributed lag nonlinear models to estimate the 21-day cumulative association between temperature and mortality in each county, 19872006, adjusting for seasonal and long-term trends, day of week, and holidays. Results: In the majority (73.4%) of counties, the relative risk of death on extremely hot days (99th percentile of weather station temperature) versus the minimum mortality temperature was larger when generated from the population-weighted estimates. In contrast, relative risks on extremely cold days (first percentile of weather station temperature) were often larger when generated from the weather station observations. In most counties, the difference in associations estimated from the two temperature metrics was small. Conclusions: In a large, multi-site analysis, temperature-mortality associations were largely similar when estimated from weather station observations versus population-weighted temperature estimates. However, spatially refined exposure data may be more appropriate for analyses seeking to elucidate local health effects. 

Research areas: Public Health
Climatological aspects of the increase of the skin cancer (melanoma) (2020)

Ultraviolet radiation (UVR) has a detrimental impact on human health. Overexposures can lead to erythema and DNA damage causing various skin cancers, including the most dangerous melanoma. Recently, a large increase in melanoma incidents has been detected in Europe. We search for a link between the increase of the skin cancer incidence rate and early spring (April) trends in surface UVR and meteorological parameters (temperature, cloudiness, and precipitation) for several European sites: Belsk (Poland), Oslo (Norway), Reading (UK), and Uccle (Belgium). The trends are calculated for the periods of 1980–2004 and 2005–2018 using ground‑based UV measurements and the reconstructed data by a multilinear regression model. The April trends are of special interest because after winter the human skin is not adapted to high UVR intensity and thus susceptible to solar exposure. Statistically insignificant UV trends are found for all stations except for Belsk with the trend of ~5% per 10 years in the former period. Positive trends of 0.5–1.0°C per 10 years (statistically significant) were calculated for all stations in the mean daily maximum temperature of April in the period 1980–2018. In April, total ozone values are negatively correlated with the daily maxima of the surface temperature, so if the temperature is higher than 15°C, the corresponding total ozone values will go below the long‑term mean, causing more intense surface UVR. Moreover, high temperatures in April may encourage people to stay longer in the sun and expose parts of the body previously covered by winter clothing, which may result in numerous sunburns yielding a higher risk of melanoma. Thus, social campaigns promoting healthy scenarios of outdoor activities should start earlier than before, that is, at the beginning of spring not just before the summer vacation.

Research areas: Public Health
Provincial and gridded population projection for China under shared socioeconomic pathways from 2010 to 2100 (2020)

In response to a growing demand for subnational and spatially explicit data on Chinas future population, this study estimates Chinas provincial population from 2010 to 2100 by age (0100+), sex (male and female) and educational levels (illiterate, primary school, junior-high school, senior-high school, college, bachelors, and masters and above) under different shared socioeconomic pathways (SSPs). The provincial projection takes into account fertility promoting policies and population ceiling restrictions of megacities that have been implemented in China in recent years to reduce systematic biases in current studies. The predicted provincial population is allocated to spatially explicit population grids for each year at 30 arc-seconds resolution based on representative concentration pathway (RCP) urban grids and historical population grids. The provincial projection data were validated using population data in 2017 from Chinas Provincial Statistical Yearbook, and the accuracy of the population grids in 2015 was evaluated. These data have numerous potential uses and can serve as inputs in climate policy research with requirements for precise administrative or spatial population data in China.

Research areas: Habitat Conversion/Fragmentation, Public Health
Developing an adaptive global exposure model to support the generation of country disaster risk profiles (2015)

Corresponding to increased realization of the impacts of natural hazards in recent years and the need for quantification of disaster risk, there has been increasing demand from the public sector for openly available disaster risk profiles. Probabilistic disaster risk profiles provide risk assessments and estimates of potential damage to property caused by severe natural hazards. These profiles outline a holistic view of financial risk due to natural hazards, assisting governments in long-term planning and preparedness. A Country Disaster Risk Profile (CDRP) presents a probabilistic estimate of risk aggregated at the national level. A critical component of a CDRP is the development of consistent and robust exposure model to complement existing hazard and vulnerability models. Exposure is an integral part of any risk assessment model, capturing the attributes of all exposed elements grouped by classes of vulnerability to different hazards, and analyzed in terms of value, location and relative importance (e.g. critical facilities and infrastructure). Using freely available (or available at minimum cost) datasets, we present a methodology for an exposure model to produce three independent geo-referenced databases to be used in national level disaster risk profiling for the public sector. These databases represent aggregated economic value at risk at 30 arc-second spatial resolution (approximately 11-km grid at the equator) using a top-down (or downscaling) approach. To produce these databases, the models used are: 1) a building inventory stock model which captures important attributes such as geographical location, urban/rural classification, type of occupancy (e.g. residential and non-residential), building typology (e.g. wood, concrete, masonry, etc.) and economic (replacement) value; 2) a non-building infrastructure density and value model that also corresponds to the fiscal infrastructure portion of the Gross Capital Stock (GCS) of a country; and 3) a spatially and sectorially disaggregated Gross Domestic Product (GDP) model that relates to the production (flow) of goods and services of a country. These models can be adapted to produce - independently or cohesively - a composite exposure database. Finally, we provide an example of the model's use in economic loss estimation for the reoccurrence of the 1882 Mw 7.8 Panama earthquake.

Research areas: Public Health
Observational evidence of the seasonal and demographic variation in experienced temperature from 77 743 UK Biobank participants (2020)

Exposure to cold is known to be associated with severe health impacts. The primary epidemiological evidence for this is the seasonal variation in mortality. However, there is a paucity of directly measured data for personal cold temperature exposure. This paper develops the concept of experienced temperature, and reports how it varies with season, demographics and housing factors.This study uses data from 77 743 UK Biobank participants. A novel method to directly measure participants exposure to low temperatures using a thermistor in a wrist-worn activity monitor is described. These readings are combined with demographic and housing factor variables in a multiple regression model to understand underlying relationships.The study reveals a significant difference in experienced temperature of ~1.8C between the periods of coldest and hottest external temperature. A number of demographic differences were also observedsuch as people of Chinese ethnic background experiencing 0.65C lower temperatures than other groups.This paper presents primary evidence for a seasonal variation in experienced temperature. This variation likely contributes to cold related mortality and morbidity. It is hypothesized that this relationship would be less strong in countries which suffer fewer impacts of cold winter temperatures.

Research areas: Public Health
Environmental factors affecting ecological niche of Coccidioides species and spatial dynamics of valley fever in the United States (2020)

Coccidioidomycosis is an understudied infectious disease acquired by inhaling fungal spores of Coccidioides species. While historically connected to the southwestern United States, the endemic region for this disease is not well defined. This study's objective was to estimate the impact of climate, soil, elevation and land cover on the Coccidioides species ecological niche. This research used maximum entropy ecological niche modeling based on disease case data from 2015 to 2016. Results found mean temperature of the driest quarter, and barren, shrub, and cultivated land covers influential in characterizing the niche. In addition to hotspots in central California and Arizona, the Columbia Plateau ecoregion of Washington and Oregon showed more favorable conditions for fungus presence than surrounding areas. The identification of influential spatial drivers will assist in future modeling efforts, and the potential distribution map generated may aid public health officials in watching for potential hotspots, assessing vulnerability, and refining endemicity.

Research areas: Public Health, Ecosystems
Quantifying the risk of local Zika virus transmission in the contiguous US during the 2015–2016 ZIKV epidemic (2018)

Local mosquito-borne Zika virus (ZIKV) transmission has been reported in two counties in the contiguous United States (US), prompting the issuance of travel, prevention, and testing guidance across the contiguous US. Large uncertainty, however, surrounds the quantification of the actual risk of ZIKV introduction and autochthonous transmission across different areas of the US.

Research areas: Public Health
How the individual human mobility spatio-temporally shapes the disease transmission dynamics (2020)

Human mobility plays a crucial role in the temporal and spatial spreading of infectious diseases. During the past few decades, researchers have been extensively investigating how human mobility affects the propagation of diseases. However, the mechanism of human mobility shaping the spread of epidemics is still elusive. Here we examined the impact of human mobility on the infectious disease spread by developing the individual-based SEIR model that incorporates a model of human mobility. We considered the spread of human influenza in two contrasting countries, namely, Belgium and Martinique, as case studies, to assess the specific roles of human mobility on infection propagation. We found that our model can provide a geo-temporal spreading pattern of the epidemics that cannot be captured by a traditional homogenous epidemic model. The disease has a tendency to jump to high populated urban areas before spreading to more rural areas and then subsequently spread to all neighboring locations. This heterogeneous spread of the infection can be captured by the time of the first arrival of the infection $$(T_{fi} )$$, which relates to the landscape of the human mobility characterized by the relative attractiveness. These findings can provide insights to better understand and forecast the disease spreading.

Research areas: Public Health
Diseases burden of chronic obstructive pulmonary disease (COPD) attributable to ground-level ozone in Thailand: estimates based on surface monitoring … (2016)

Background:
Ambient ozone (O3) pollution has increased globally since preindustrial times. At present, O3 is one of the major air pollution concerns in Thailand, and is associated with health impacts such as chronic obstructive pulmonary disease (COPD). The objective of our study is to estimate the burden of disease attributed to O3 in 2009 in Thailand based on empirical evidence.

Methods:
We estimated disability-adjusted life years (DALYs) attributable to O3 using the comparative risk assessment framework in the Global Burden of Diseases (GBD) study. We quantified the population attributable fraction (PAF), integrated from Geographic Information Systems (GIS)-based spatial interpolation, the population distribution of exposure, and the exposure-response coefficient to spatially characterize exposure to ambient O3 pollution on a national scale. Exposure distribution was derived from GIS-based spatial interpolation O3 exposure model using Pollution Control Department Thailand (PCD) surface air pollution monitor network sources. Relative risk (RR) and population attributable fraction (PAF) were determined using health impact function estimates for O3.

Result:
PAF (%) of COPD attributable to O3 were determined by region: at approximately, Northern = 2.1, Northeastern = 7.1, Central = 9.6, Eastern = 1.75, Western = 1.47 and Southern = 1.74. The total COPD burden attributable to O3 for Thailand in 2009 was 61,577 DALYs. Approximately 0.6% of the total DALYs in Thailand is male: 48,480 DALYs; and female: 13,097 DALYs.

Conclusion:
This study provides the first empirical evidence on the health burden (DALYs) attributable to O3 pollution in Thailand. Varying across regions, the disease burden attributable to O3 was 0.6% of the total national burden in 2009. Better empirical data on local specific sites, e.g. urban and rural areas, alternative exposure assessment, e.g. land use regression (LUR), and a local concentration-response coefficient are required for future studies in Thailand.

Research areas: Public Health, Air Quality
Global distribution of forest classes and leaf biomass for use as alternative foods to minimize malnutrition (2021)

AbstractDue to the ready availability of tree leaves in many geographies, the alternative food of leaf concentrate currently has the potential to alleviate hunger in over 800 million people. It is therefore potentially highly impactful to determine the edibility of leaf concentrates, which are in the same regions as the world's most undernourished populations. Unfortunately, the toxicity of leaf concentrate for most common tree leaf types has not been screened and the cost of doing so demands a prioritization. This preliminary study explores this potential solution to world hunger by finding the forest classes most likely to offer proximate access to the world's hungry, thus providing the basis for a prioritized list of leaf types to screen for toxicity. Specifically, this study describes a novel methodology for mapping available green leaf biomass and corresponding forest classes (e.g., tropical moist deciduous forest), and their spatial relationship to the global distribution of people who are underweight. These results will be useful for developing a targeted list of tree species to conduct leaf toxicity analysis on, in the interest of developing leaves as an alternative food source for both current malnutrition problems and global catastrophic scenarios.

Research areas: Public Health
Validation of the TROPOspheric Monitoring Instrument (TROPOMI) surface UV radiation product (2020)

Abstract. The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (S5P) satellite was launched on 13 October 2017 to provide the atmospheric composition for atmosphere and climate research. The S5P is a Sun-synchronous polar-orbiting satellite providing global daily coverage. The TROPOMI swath is 2600 km wide, and the ground resolution for most data products is 7.23.5 km2 (5.63.5 km2 since 6 August 2019) at nadir. The Finnish Meteorological Institute (FMI) is responsible for the development of the TROPOMI UV algorithm and the processing of the TROPOMI surface ultraviolet (UV) radiation product which includes 36 UV parameters in total. Ground-based data from 25 sites located in arctic, subarctic, temperate, equatorial and Antarctic areas were used for validation of the TROPOMI overpass irradiance at 305, 310, 324 and 380 nm, overpass erythemally weighted dose rate/UV index, and erythemally weighted daily dose for the period from 1 January 2018 to 31 August 2019. The validation results showed that for most sites 60 %80 % of TROPOMI data was within 20 % of ground-based data for snow-free surface conditions. The median relative differences to ground-based measurements of TROPOMI snow-free surface daily doses were within 10 % and 5 % at two-thirds and at half of the sites, respectively. At several sites more than 90 % of cloud-free TROPOMI data was within 20 % of ground-based measurements. Generally median relative differences between TROPOMI data and ground-based measurements were a little biased towards negative values (i.e. satellite data < ground-based measurement), but at high latitudes where non-homogeneous topography and albedo or snow conditions occurred, the negative bias was exceptionally high: from 30 % to 65 %. Positive biases of 10 %15 % were also found for mountainous sites due to challenging topography. The TROPOMI surface UV radiation product includes quality flags to detect increased uncertainties in the data due to heterogeneous surface albedo and rough terrain, which can be used to filter the data retrieved under challenging conditions.

Research areas: Validation
Exploring country-wide equitable government health care facility access in Uganda (2021)

Rural access to health care remains a challenge in Sub-Saharan Africa due to urban bias, social determinants of health, and transportation-related barriers. Health systems in Sub-Saharan Africa often lack equity, leaving disproportionately less health center access for the poorest residents with the highest health care needs. Lack of health care equity in Sub-Saharan Africa has become of increasing concern as countries enter a period of simultaneous high infectious and non-communicable disease burdens, the second of which requires a robust primary care network due to a long continuum of care. Bicycle ownership has been proposed and promoted as one tool to reduce travel-related barriers to health-services among the poor.

Research areas: Public Health