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| 2. |
- Brimicombe, Chloe, et al.
(författare)
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Wet Bulb Globe Temperature : Indicating Extreme Heat Risk on a Global Grid
- 2023
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Ingår i: GeoHealth. - : American Geophysical Union (AGU). - 2471-1403. ; 7:2
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Tidskriftsartikel (refereegranskat)abstract
- The Wet Bulb Globe Temperature (WBGT) is an international standard heat index used by the health, industrial, sports, and climate sectors to assess thermal comfort during heat extremes. Observations of its components, the globe and the wet bulb temperature (WBT), are however sparse. Therefore WBGT is difficult to derive, making it common to rely on approximations, such as the ones developed by Liljegren et al. and by the American College of Sports Medicine (WBGT(ACSM87)). In this study, a global data set is created by implementing an updated WBGT method using ECMWF ERA5 gridded meteorological variables and is evaluated against existing WBGT methods. The new method, WBGT(Brimicombe), uses globe temperature calculated using mean radiant temperature and is found to be accurate in comparison to WBGT(Liljegren) across three heatwave case studies. In addition, it is found that WBGT(ACSM87) is not an adequate approximation of WBGT. Our new method is a candidate for a global forecasting early warning system.
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| 3. |
- DiSera, Laurel, et al.
(författare)
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The Mosquito, the Virus, the Climate : An Unforeseen Réunion in 2018
- 2020
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Ingår i: GeoHealth. - : John Wiley & Sons. - 2471-1403. ; 4:8
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Tidskriftsartikel (refereegranskat)abstract
- The 2018 outbreak of dengue in the French overseas department of Réunion was unprecedented in size and spread across the island. This research focuses on the cause of the outbreak, asserting that climate played a large role in the proliferation of the Aedes albopictus mosquitoes, which transmitted the disease, and led to the dengue outbreak in early 2018. A stage‐structured model was run using observed temperature and rainfall data to simulate the life cycle and abundance of the Ae. albopictus mosquito. Further, the model was forced with bias‐corrected subseasonal forecasts to determine if the event could have been forecast up to 4 weeks in advance. With unseasonably warm temperatures remaining above 25°C, along with large tropical‐cyclone‐related rainfall events accumulating 10–15 mm per event, the modeled Ae. albopictus mosquito abundance did not decrease during the second half of 2017, contrary to the normal behavior, likely contributing to the large dengue outbreak in early 2018. Although subseasonal forecasts of rainfall for the December–January period in Réunion are skillful up to 4 weeks in advance, the outbreak could only have been forecast 2 weeks in advance, which along with seasonal forecast information could have provided enough time to enhance preparedness measures. Our research demonstrates the potential of using state‐of‐the‐art subseasonal climate forecasts to produce actionable subseasonal dengue predictions. To the best of the authors' knowledge, this is the first time subseasonal forecasts have been used this way.
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| 4. |
- Ebert, Karin, 1976-, et al.
(författare)
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Lower COVID‐19 Incidence in Low‐Continentality West‐Coast Areas of Europe
- 2022
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Ingår i: GeoHealth. - : American Geophysical Union (AGU). - 2471-1403. ; 6:5
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Tidskriftsartikel (refereegranskat)abstract
- In March 2020, the first known cases of COVID-19 occurred in Europe. Subsequently, the pandemic developed a seasonal pattern. The incidence of COVID-19 comprises spatial heterogeneity and seasonal variations, with lower and/or shorter peaks resulting in lower total incidence and higher and/or longer peaks resulting higher total incidence. The reason behind this phenomena is still unclear. Unraveling factors that explain why certain places have higher versus lower total COVID-19 incidence can help health decision makers understand and plan for future waves of the pandemic. We test whether differences in the total incidence of COVID-19 within five European countries (Norway, Sweden, Germany, Italy, and Spain), correlate with two environmental factors: the Köppen-Geiger climate zones and the Continentality Index, while statistically controlling for crowding. Our results show that during the first 16 months of the pandemic (March 2020 to July 2021), climate zones with larger annual differences in temperature and annually distributed precipitation show a higher total incidence than climate zones with smaller differences in temperature and dry seasons. This coincides with lower continentality values. Total incidence increases with continentality, up to a Continentality Index value of 19, where a peak is reached in the semicontinental zone. Low continentality (high oceanic influence) appears to be a strong suppressing factor for COVID-19 spread. The incidence in our study area is lowest at open low continentality west coast areas.
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| 6. |
- Ferrara, Vincenza, et al.
(författare)
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The Entangled Phenology of the Olive Tree : A Compiled Ecological Calendar of Olea Europaea L. Over the Last Three Millennia With Sicily as a Case Study
- 2023
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Ingår i: GeoHealth. - : American Geophysical Union (AGU). - 2471-1403. ; 7:3
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Tidskriftsartikel (refereegranskat)abstract
- Seasonal cycles in plants and animals drive key timings of human practices in an agrosystem like the best time for harvest, planting, or pruning. Within the framework of historical phenological studies, we attempt a reconstruction of the olive (Olea europaea L.) phenology along millennia. Thanks to its extraordinary longevity, the olive tree is a living proxy from the past and embodies a still uncollected long-term memory of ecological behaviors. A cultural keystone species, olive cultivation has more and more played a crucial role for biodiversity conservation, livelihood of rural communities and their enrooted cultural identity in the whole Mediterranean. By compiling traditional phenological knowledge from historical written sources and oral traditions, and using it as historical bio-indicator of the linkage between human ecological practices and seasonal changes of plant behavior, we compiled a monthly ecological calendar of the olive tree covering the last similar to 2800 years. As a case study, we chose a special place: Sicily, unique for its position in the Mediterranean, geomorphology and legacies in the form of cross-temporal accumulated eco-cultures. Such a sui generis ecological calendar provides an additional case study to explore the intertwining of plant behavior and human adaptation strategies and the interplay between cultural diversity, ecological disturbance and phenological stability. All of this, in turn, can inform action for the present and future sustainable management of these millennial trees.
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| 7. |
- Kalthof, Maurice W. M. L., et al.
(författare)
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Predicting Continental Scale Malaria With Land Surface Water Predictors Based on Malaria Dispersal Mechanisms and High-Resolution Earth Observation Data
- 2023
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Ingår i: GeoHealth. - 2471-1403. ; 7:10
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Tidskriftsartikel (refereegranskat)abstract
- Despite malaria prevalence being linked to surface water through vector breeding, spatial malaria predictors representing surface water often predict malaria poorly. Furthermore, precipitation, which precursors surface water, often performs better. Our goal is to determine whether novel surface water exposure indices that take malaria dispersal mechanisms into account, derived from new high-resolution surface water data, can be stronger predictors of malaria prevalence compared to precipitation. One hundred eighty candidate predictors were created by combining three surface water malaria exposures from high-accuracy and resolution (5 m resolution, overall accuracy 96%, Kappa Coefficient 0.89, Commission and Omission error 3% and 13%, respectively) water maps of East Africa. Through variable contribution analysis a subset of strong predictors was selected and used as input for Boosted Regression Tree models. We benchmarked the performance and Relative Contribution of this set of novel predictors to models using precipitation instead of surface water predictors, alternative lower resolution predictors, and simpler surface water predictors used in previous studies. The predictive performance of the novel indices rivaled or surpassed that of precipitation predictors. The novel indices substantially improved performance over the identical set of predictors derived from the lower resolution Joint Research Center surface water data set (+10% R2, +17% Relative Contribution) and over the set of simpler predictors (+18% R2, +30% Relative Contribution). Surface water derived indices can be strong predictors of malaria, if the spatial resolution is sufficiently high to detect small waterbodies and dispersal mechanisms of malaria related to surface water in human and vector water exposure assessment are incorporated.
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| 8. |
- Lagunas-Rangel, Francisco Alejandro, et al.
(författare)
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Role of the synergistic interactions of environmental pollutants in the development of cancer
- 2022
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Ingår i: GeoHealth. - : American Geophysical Union (AGU). - 2471-1403. ; 6:4
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Forskningsöversikt (refereegranskat)abstract
- There is a growing awareness that the large number of environmental pollutants we are exposed to on a daily basis are causing major health problems. Compared to traditional studies that focus on individual pollutants, there are relatively few studies on how pollutants mixtures interact. Several studies have reported a relationship between environmental pollutants and the development of cancer, even when pollutant levels are below toxicity reference values. The possibility of synergistic interactions between different pollutants could explain how even low concentrations can cause major health problems. These intricate that molecular interactions can occur through a wide variety of mechanisms, and our understanding of the physiological effects of mixtures is still limited. The purpose of this paper is to discuss recent reports that address possible synergistic interactions between different types of environmental pollutants that could promote cancer development. Our literature studies suggest that key biological pathways are frequently implicated in such processes. These include increased production of reactive oxygen species, activation by cytochrome P450, and aryl hydrocarbon receptor signaling, among others. We discuss the need to understand individual pathological vulnerability not only in relation to basic genetics and gene expression, but also in terms of measurable exposure to contaminants. We also mention the need for significant improvements in future studies using a multitude of disciplines, such as the development of high-throughput study models, better tools for quantifying pollutants in cancer patients, innovative pharmacological and toxicological studies, and high-efficiency computer analysis, which allow us to analyze the molecular mechanisms of mixtures.Plain Language SummaryIn general, every day we are exposed to many pollutants at the same time, and each pollutant can interact with others in different ways. Notably, two or more pollutants can interact and enhance their effects through a phenomenon called synergy and this would explain why, even at low concentrations, pollutants can have important health effects. Several studies have reported a link between environmental pollutants and cancer. Thus, our review of the literature suggests that synergy phenomena between pollutants can alter key points in cells and facilitate cancer development. Similarly, we mention the complications and needs to assess these complex interactions in subsequent studies.
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| 9. |
- Ma, Y., et al.
(författare)
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Infectious Disease Sensitivity to Climate and Other Driver-Pressure Changes : Research Effort and Gaps for Lyme Disease and Cryptosporidiosis
- 2023
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Ingår i: GeoHealth. - : American Geophysical Union (AGU). - 2471-1403. ; 7:6
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Forskningsöversikt (refereegranskat)abstract
- Climate sensitivity of infectious diseases is discussed in many studies. A quantitative basis for distinguishing and predicting the disease impacts of climate and other environmental and anthropogenic driver-pressure changes, however, is often lacking. To assess research effort and identify possible key gaps that can guide further research, we here apply a scoping review approach to two widespread infectious diseases: Lyme disease (LD) as a vector-borne and cryptosporidiosis as a water-borne disease. Based on the emerging publication data, we further structure and quantitatively assess the driver-pressure foci and interlinkages considered in the published research so far. This shows important research gaps for the roles of rarely investigated water-related and socioeconomic factors for LD, and land-related factors for cryptosporidiosis. For both diseases, the interactions of host and parasite communities with climate and other driver-pressure factors are understudied, as are also important world regions relative to the disease geographies; in particular, Asia and Africa emerge as main geographic gaps for LD and cryptosporidiosis research, respectively. The scoping approach developed and gaps identified in this study should be useful for further assessment and guidance of research on infectious disease sensitivity to climate and other environmental and anthropogenic changes around the world.
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| 10. |
- Morlighem, Camille, et al.
(författare)
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Spatial Optimization Methods for Malaria Risk Mapping in Sub-Saharan African Cities Using Demographic and Health Surveys
- 2023
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Ingår i: GeoHealth. - : American Geophysical Union (AGU). - 2471-1403. ; 7:10
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Tidskriftsartikel (refereegranskat)abstract
- Vector-borne diseases, such as malaria, are affected by the rapid urban growth and climate change in sub-Saharan Africa (SSA). In this context, intra-urban malaria risk maps act as a key decision-making tool for targeting malaria control interventions, especially in resource-limited settings. The Demographic and Health Surveys (DHS) provide a consistent malaria data source for mapping malaria risk at the national scale, but their use is limited at the intra-urban scale because survey cluster coordinates are randomly displaced for ethical reasons. In this research, we focus on predicting intra-urban malaria risk in SSA cities-Dakar, Dar es Salaam, Kampala and Ouagadougou-and investigate the use of spatial optimization methods to overcome the effect of DHS spatial displacement. We modeled malaria risk using a random forest regressor and remotely sensed covariates depicting the urban climate, the land cover and the land use, and we tested several spatial optimization approaches. The use of spatial optimization mitigated the effects of DHS spatial displacement on predictive performance. However, this comes at a higher computational cost, and the percentage of variance explained in our models remained low (around 30%-40%), which suggests that these methods cannot entirely overcome the limited quality of epidemiological data. Building on our results, we highlight potential adaptations to the DHS sampling strategy that would make them more reliable for predicting malaria risk at the intra-urban scale. Global climate change and rapid urbanization in sub-Saharan Africa (SSA) are likely to affect the epidemiology of vector-borne diseases such as malaria in urban and peri-urban areas. In this context, a better understanding of intra-urban malaria risk and its determinants has become even more urgent. Malaria risk has often been modeled at the national scale from Demographic and Health Surveys (DHS), which are periodically conducted in more than 90 developing countries. However, survey cluster coordinates in DHS are randomly displaced by up to 2 km in urban areas to protect respondent privacy, which reduces the accuracy of malaria models and risk maps at the intra-urban scale. In this study, we tested the potential of spatial optimization methods to overcome the effect of DHS displacement. We found that spatial optimization methods improved the performance of malaria models, but the improvement in performance is small for a higher computational cost. With these methods, we predicted malaria risk in several SSA cities (Dakar, Dar es Salaam, Kampala and Ouagadougou). We expect the quality and quantity of available data on malaria and other vector-borne diseases to improve in the future, which will certainly make these methods extremely useful in the fight against these diseases. We tested spatial optimization approaches to overcome the effect of cluster spatial displacement in Demographic and Health Surveys (DHS)Spatial optimization reduced the effect of displacement, but the percentage of variance explained in malaria models remained lowWe proposed potential adaptations to the DHS sampling strategy to better support the study of malaria risk at the intra-urban scale.
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