Mapping climate change interaction with human health through DPSIR framework: Qatar perspective

This study investigates the interactions between climate change and human health with a particular focus on Qatar, using the DPSIR (Driving Forces, Pressures, States, Impacts, Responses) framework. Key drivers, including economic development and population growth, contribute to increased greenhouse gas (GHG) emissions, exerting pressure on Qatar's climate through rising temperatures and altered precipitation patterns, as modeled by the MIT Regional Climate Model (MRCM). The findings reveal critical gaps in understanding the state of climate-health interactions, including insufficient disease data, incomplete climate-health linkages, and significant research gaps. These limitations hinder targeted responses to climate-sensitive diseases, which have shown an increase over the years. The study identifies the pathways through which climatic shifts contribute to immediate health risks, such as heat-related illnesses and respiratory conditions, as well as long-term impacts, including chronic diseases and mental health challenges. Despite Qatar's efforts through national and international strategies, the DPSIR analysis highlights the urgent need for enhanced research, improved data collection, and tailored actions to address these challenges. Strengthened adaptation, resilience-building, and emission reduction strategies remain essential for safeguarding public health in the face of accelerating climate change.

Shedding light on development: Leveraging the new nightlights data to measure economic progress

Nightlights (NTL) have been widely used as a proxy for economic activity, despite known limitations in accuracy and comparability, particularly with outdated Defense Meteorological Satellite Program (DMSP) data. The emergence of newer and more precise Visible Infrared Imaging Radiometer Suite (VIIRS) data offers potential, yet challenges persist due to temporal and spatial disparities between the two datasets. Addressing this, we employ a novel harmonized NTL dataset (VIIRS + DMSP), which provides the longest and most consistent database available to date. We evaluate the association between newly available harmonized NTL data and various indicators of economic activity at the subnational level across 34 countries in sub-Saharan Africa from 2004 to 2019. Specifically, we analyze the accuracy of the new NTL data in predicting socio-economic outcomes obtained from two sources: 1) nationally representative surveys, i.e., the household Wealth Index published by Demographic and Health Surveys, and 2) indicators derived from administrative records such as the gridded Human Development Index and Gross Domestic Product per capita. Our findings suggest that even after controlling for population density, the harmonized NTL remain a strong predictor of the wealth index. However, while urban areas show a notable association between harmonized NTL and the wealth index, this relationship is less pronounced in rural areas. Furthermore, we observe that NTL can also significantly explain variations in both GDP per capita and HDI at subnational levels.

Assessing the ecological resilience of Ebola virus in Africa and potential influencing factors based on a synthesized model

BACKGROUND

The Ebola epidemic has persisted in Africa since it was firstly identified in 1976. However, few studies have focused on spatiotemporally assessing the ecological adaptability of this virus and the influence of multiple factors on outbreaks. This study quantitatively explores the ecological adaptability of Ebola virus and its response to different potential natural and anthropogenic factors from a spatiotemporal perspective.

METHODOLOGY

Based on historical Ebola cases and relevant environmental factors collected from 2014 to 2022 in Africa, the spatiotemporal distribution of Ebola adaptability is characterized by integrating four distinct ecological models into one synthesized spatiotemporal framework. Maxent and Generalized Additive Models were applied to further reveal the potential responses of the Ebola virus niche to its ever-changing environments.

FINDINGS

Ebola habitats appear to aggregate across the sub-Saharan region and in north Zambia and Angola, covering approximately 16% of the African continent. Countries presently unaffected by Ebola but at increasing risk include Ethiopia, Tanzania, Côte d'Ivoire, Ghana, Cameroon, and Rwanda. In addition, among the thirteen key influencing factors, temperature seasonality and population density were identified as significantly influencing the ecological adaptability of Ebola. Specifically, those regions were prone to minimal seasonal variations in temperature. Both the potential anthropogenic influence and vegetation coverage demonstrate a rise-to-decline impact on the outbreaks of Ebola virus across Africa.

CONCLUSIONS

Our findings suggest new ways to effectively respond to potential Ebola outbreaks in Sub-Saharan Africa. We believe that this integrated modeling approach and response analysis provide a framework that can be extended to predict risk of other worldwide diseases from a similar epidemic study perspective.

Determinants of viral haemorrhagic fever risk in Africa's tropical moist forests: A scoping review of spatial, socio-economic, and environmental factors

BACKGROUND

Viral haemorrhagic fevers (VHFs) are identified by international health authorities as priorities for research and development, as they pose a threat to global health and economy. VHFs are zoonotic diseases whose acute forms in humans present a haemorrhagic syndrome and shock, with mortality rates of up to 90%. This work aims at synthetizing existing knowledge on spatial and spatially aggregable determinants that support the emergence and maintenance of VHFs in African countries covered by tropical moist forest, to better identify and map areas at risk.

METHODOLOGY/PRINCIPAL FINDINGS

Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA-ScR) guidelines, extension for scoping reviews, we searched the PubMed, Embase, CAB Abstracts, and Scopus databases. English and French peer-reviewed documents were retrieved using Boolean logic and keyword search terms. The analysis of 79 articles published between 1993 and 2023 offers a comprehensive overview of the complex interactions among abiotic, biotic, demographic, socio-economic, cultural, and political risk factors in driving the emergence and maintenance of VHFs in African countries covered by tropical moist forests. Human-to-human transmission is mainly driven by socio-economic, political, and demographic factors, whereas zoonotic spillover is determined by almost all groups of factors, especially those of an anthropogenic nature.

CONCLUSIONS/SIGNIFICANCE

Many questions remain unanswered regarding the epidemiology of VHFs in tropical forests. By elucidating spatially relevant determinants which have already been studied, this review seeks to advance VHFs hotspot predictions, risk mapping for disease surveillance and control systems improvement.

Plague risk in the western United States over seven decades of environmental change

After several pandemics over the last two millennia, the wildlife reservoirs of plague (Yersinia pestis) now persist around the world, including in the western United States. Routine surveillance in this region has generated comprehensive records of human cases and animal seroprevalence, creating a unique opportunity to test how plague reservoirs are responding to environmental change. Here, we test whether animal and human data suggest that plague reservoirs and spillover risk have shifted since 1950. To do so, we develop a new method for detecting the impact of climate change on infectious disease distributions, capable of disentangling long-term trends (signal) and interannual variation in both weather and sampling (noise). We find that plague foci are associated with high-elevation rodent communities, and soil biochemistry may play a key role in the geography of long-term persistence. In addition, we find that human cases are concentrated only in a small subset of endemic areas, and that spillover events are driven by higher rodent species richness (the amplification hypothesis) and climatic anomalies (the trophic cascade hypothesis). Using our detection model, we find that due to the changing climate, rodent communities at high elevations have become more conducive to the establishment of plague reservoirs-with suitability increasing up to 40% in some places-and that spillover risk to humans at mid-elevations has increased as well, although more gradually. These results highlight opportunities for deeper investigation of plague ecology, the value of integrative surveillance for infectious disease geography, and the need for further research into ongoing climate change impacts.

Investigation of Ebolavirus exposure in pigs presented for slaughter in Uganda

In 2008, an outbreak of Reston ebolavirus (RESTV) in pigs in the Philippines expanded our understanding of the host range of ebolaviruses. Subsequent experimental infections with the human‐pathogenic species Zaire ebolavirus (EBOV) confirmed that pigs are susceptible to African species of ebolaviruses. Pig keeping has become an increasingly important livelihood strategy throughout parts of sub‐Saharan Africa, driven by increasing demand for pork. The growth in pig keeping is particularly rapid in Uganda, which has the highest per capita pork consumption in East Africa and a history of sporadic human outbreaks of Ebola virus disease (EVD). Using a systematic sampling protocol, we collected sera from 658 pigs presented for slaughter in Uganda between December 2015 and October 2016. Forty‐six pigs (7%) were seropositive based on ELISA tests at two different institutions. Seropositive pigs had antibodies that bound to Sudan NP (n = 27), Zaire NP (Kikwit; n = 8) or both NPs (n = 11). Sera from 4 of the ELISA‐positive pigs reacted in Western blot (EBOV NP = 1; RESTV NP = 2; both NPs = 2), and one sample had full neutralizing antibody against Sudan ebolavirus (SUDV) in virus neutralization tests. Pigs sampled in June 2016 were significantly more likely to be seropositive than pigs sampled in October 2016 (p = .03). Seropositive pigs were sourced from all regions except Western region. These observed temporal and spatial variations are suggestive of multiple introductions of ebolaviruses into the pig population in Uganda. This is the first report of exposure of pigs in Uganda to ebolaviruses and the first to employ systematic abattoir sampling for ebolavirus surveillance during a non‐outbreak period. Future studies will be necessary to further define the role pigs play (if any) in ebolavirus maintenance and transmission so that potential risks can be mitigated.

Translating Predictions of Zoonotic Viruses for Policymakers

Recent outbreaks of Ebola virus disease and Zika virus disease highlight the need for disseminating accurate predictions of emerging zoonotic viruses to national governments for disease surveillance and response. Although there are published maps for many emerging zoonotic viruses, it is unknown if there is agreement among different models or if they are concordant with national expert opinion. Therefore, we reviewed existing predictions for five high priority emerging zoonotic viruses with national experts in Cameroon to investigate these issues and determine how to make predictions more useful for national policymakers. Predictive maps relied primarily on environmental parameters and species distribution models. Rift Valley fever virus and Crimean-Congo hemorrhagic fever virus predictions differed from national expert opinion, potentially because of local livestock movements. Our findings reveal that involving national experts could elicit additional data to improve predictions of emerging pathogens as well as help repackage predictions for policymakers.