Climate change and infectious diseases in Europe

Increasing trends in faecal pollution revealed over a decade in the central Adriatic Sea (Italy)

Faecal contamination of the coastal sea poses widespread hazard to human and environmental health and is predicted to rise in response to global change and human pressure. For better management and risk reduction it is thus imperative to clarify and predict trends of faecal pollution over spatial and temporal scales, and to assess links with climate and other variables. Here, we investigated the spatio-temporal variation in the Faecal Indicator Bacteria (FIB) Escherichia coli and enterococci, over a time frame spanning 11 years (2011-2021) along a coastal area covering approximately 40 km and 59 bathing sites in the Marche region (Adriatic Sea, Italy), characterized by intense beach tourism, high riverine inputs, resident population, maritime traffic and industrial activities. Our analysis, that considers 5,183 measurements during the bathing season (April to October), shows that FIB abundance varied significantly among years. A general, although not significant, increase over time of both FIB was observed, mainly due to a general reduction of structural zeros (i.e., zeros originated from the actual absence of the response variable) over the examined time period. FIB abundances displayed their maxima and minima in different years according to the municipality, with overall peaks recorded in different months (May-June or September), whereas the lowest values were always observed in October. FIB levels were not significantly related neither to rainfalls nor to river discharge, but the activation of combined sewer overflows (CSOs), typically occurring after intense rainfall events, appeared as a necessary condition for the high faecal contamination levels. Considering climate change scenarios predicting significant increases in extreme weather events, our findings support the usefulness of analysing long-term trends to identify pollution sources, and the prioritization of control strategies to better manage the release of microbial pollutants from combined sewer overflows in coastal waters to reduce human risks.

Beyond Borders: Dirofilaria immitis Infection in Dogs Spreads to Previously Non-Enzootic Areas in Greece-A Serological Survey

Although Dirofilaria immitis in dogs is considered enzootic in northern Greece, the available data on the occurrence of infection in southern parts of the country demonstrate its scarcity. The aim of this study was to update the current knowledge on D. immitis infection in dogs in areas of Greece previously considered non-enzootic (Central Greece, Attica, Peloponnese, North Aegean, South Aegean, Crete and the Ionian islands). In total, 1528 dog blood samples were collected from the aforementioned areas and examined by Dirochek® ELISA (Synbiotics). Additionally, data published until 2022 on the prevalence of infection in these areas were compared to the data of this study. The 'Wilson' Score interval method (Epitools) was employed. Overall, 10.8% of dogs were positive for D. immitis. In detail, the prevalence was 21.7, 13.7, 10.7, 5.4, 4.7, 6.2 and 17.0% for D. immitis, in Central Greece, Attica, Peloponnese, North Aegean, South Aegean, Crete and the Ionian islands, respectively. Infection with D. immitis is recorded for the first time in Crete. The probability of a dog becoming infected has increased 4.1 times since 2022 in previously non-enzootic areas. This study denotes the spread of D. immitis and highlights the necessity for preventive measures.

Ecological niche modeling analysis (Cx. pipiens), potential risk and projection of Dirofilaria spp. infection in Greece

Vector-borne diseases continue to increase worldwide. Dirofilariosis is one of the most common vector-borne zoonotic diseases, mainly caused by Dirofilaria spp. (D. immitis and D. repens) and spread by culicid mosquitoes of different species. Greece is one of the countries in southern Europe where it is traditionally endemic, and its distribution is not homogeneous. The aim of this study was to develop an environmental model for Greece that reflects the suitability of the ecological niche for Dirofilaria spp. infection risk and its projection until 2080. For this purpose, we used the potential distribution of suitable habitats for Culex pipiens calculated using an ecological niche model (ENM) and the potential number of generations of Dirofilaria spp. The ecological niche model of Cx. pipiens in Greece showed good predictive power (AUC=0.897) with the parasite at a resolution of 1 km2. The variables that contributed most to the model were mean annual temperature, rivers and human footprint. The highest risk of infection was found in coastal areas and in riverside areas of the main river basins, as well as in irrigated areas of the mainland and peninsular regions and in the whole territory of island areas, and the lowest risk was found in areas of higher altitude. A positive relationship was found between the risk of dirofilariosis and the location of infected dogs, with 86.65% located in very high and high risk areas. In 2080, the percentage of territory gained by Cx. pipiens will increase by 261.52%. This model provides a high predictive value, predicted presence, and risk of Dirofilaria spp. infection and can serve as a tool for the management and control of this disease.

Expanding the focus of the One Health concept: links between the Earth-system processes of the planetary boundaries framework and antibiotic resistance

The scientific community warns that our impact on planet Earth is so acute that we are crossing several of the planetary boundaries that demarcate the safe operating space for humankind. Besides, there is mounting evidence of serious effects on people's health derived from the ongoing environmental degradation. Regarding human health, the spread of antibiotic resistant bacteria is one of the most critical public health issues worldwide. Relevantly, antibiotic resistance has been claimed to be the quintessential One Health issue. The One Health concept links human, animal, and environmental health, but it is frequently only focused on the risk of zoonotic pathogens to public health or, to a lesser extent, the impact of contaminants on human health, i.e., adverse effects on human health coming from the other two One Health "compartments". It is recurrently claimed that antibiotic resistance must be approached from a One Health perspective, but such statement often only refers to the connection between the use of antibiotics in veterinary practice and the antibiotic resistance crisis, or the impact of contaminants (antibiotics, heavy metals, disinfectants, etc.) on antibiotic resistance. Nonetheless, the nine Earth-system processes considered in the planetary boundaries framework can be directly or indirectly linked to antibiotic resistance. Here, some of the main links between those processes and the dissemination of antibiotic resistance are described. The ultimate goal is to expand the focus of the One Health concept by pointing out the links between critical Earth-system processes and the One Health quintessential issue, i.e., antibiotic resistance.

Characterization and Seasonal Dynamics of Tick Populations in Dairy Cattle Production Systems of Northwestern Colombian Amazon

Cattle ticks are a significant health concern in tropical livestock production due to their hematophagous behavior and potential as vectors for human and animal pathogens. In this study, we investigated the tick population present in dairy cattle production, calves, and grazing areas of livestock systems in the northwestern Colombian Amazon. Identification was based on taxonomic keys and molecular markers. Phylogenetic relationships were established using mitochondrial COX1 and 16S genes. Population structure analysis was performed considering age, racial type (B. indicus vs. B. taurus), and the influence of environmental factors and the geomorphological landscape on tick population dynamics. Our findings revealed the presence of a single tick species, with a unique haplotype identified for each mitochondrial gene assessed. Phylogenetic analysis classified the found species within Clade A of the Rhipicephalus microplus complex. Ticks were more prevalent during periods of low rainfall and high temperature, and B. taurus cows exhibited the highest tick abundance. Thus, these results provide insights into the population characteristics and distribution of the tick species present in dairy cattle production systems in the northwestern part of the Colombian Amazon. This information is fundamental for developing targeted strategies based on seasonal variation and host characteristics to mitigate tick infestation severity in the region.

Analysis of the current risk of Leishmania infantum transmission for domestic dogs in Spain and Portugal and its future projection in climate change scenarios

Canine leishmaniosis, caused by the protozoan parasite Leishmania infantum, is a cosmopolitan vector-borne zoonosis, transmitted principally by Phlebotomus perniciosus in Spain and Portugal, where it is considered an endemic disease. Ecoinformatics tools such as ecological niche models (ENM) have been successfully tested to model the distribution of the risk of infection of different parasitosis as they take into account environmental variables vital for their survival. The risk map proposed in this study combines the potential distribution of Ph. perniciosus in the Iberian Peninsula and the calculation of the infection rate of the parasite in the vector to model the risk of contracting the disease in a more realistic way. In fact, this weighting strategy improves the predictive power of the resulting model (R2 = 0.42, p = < 0.01) compared to the Ph. perniciosus ENM model alone (R2 = 0.13, p > 0.05). The places with the highest risk of transmission are the southwest and central peninsular area, as well as the Mediterranean coast, the Balearic Islands and the Ebro basin, places where the ideal habitat of Ph. perniciosus and the infection rate is also high. In the case of future projections under climate change scenarios, an increase in the risk of infection by L. infantum can be observed in most of the territory (4.5% in 2040, 71.6% in 2060 and 63% in 2080), mainly in the northern part of the peninsula. The use of ENMs and their weighting with the infection rate in Ph. perniciosus is a useful tool in predicting the risk of infection for L. infantum in dogs for a given area. In this way, a more complete model can be obtained to facilitate prevention and control.

Contribution of climate change to the spatial expansion of West Nile virus in Europe

West Nile virus (WNV) is an emerging mosquito-borne pathogen in Europe where it represents a new public health threat. While climate change has been cited as a potential driver of its spatial expansion on the continent, a formal evaluation of this causal relationship is lacking. Here, we investigate the extent to which WNV spatial expansion in Europe can be attributed to climate change while accounting for other direct human influences such as land-use and human population changes. To this end, we trained ecological niche models to predict the risk of local WNV circulation leading to human cases to then unravel the isolated effect of climate change by comparing factual simulations to a counterfactual based on the same environmental changes but a counterfactual climate where long-term trends have been removed. Our findings demonstrate a notable increase in the area ecologically suitable for WNV circulation during the period 1901-2019, whereas this area remains largely unchanged in a no-climate-change counterfactual. We show that the drastic increase in the human population at risk of exposure is partly due to historical changes in population density, but that climate change has also been a critical driver behind the heightened risk of WNV circulation in Europe.

The association between climatic factors and waterborne infectious outbreaks with a focus on vulnerability in Pakistan: integrative review

Climate change affects the spread of waterborne infectious diseases, yet research on vulnerability to outbreaks remains limited. This integrative review examines how climate variables (temperature and precipitation) relate to human vulnerability factors in Pakistan. By 2060, mean temperatures are projected to rise from 21.68°C (2021) to 30°C, with relatively stable precipitation. The epidemiological investigation in Pakistan identified Diarrhea (119,000 cases/year), Malaria (2.6 million cases/year), and Hepatitis (A and E) as the most prevalent infections. This research highlighted vulnerability factors, including poverty (52% of the population), illiteracy (59% of the population), limited healthcare accessibility (55% of the population), malnutrition (38% of the population), dietary challenges (48% of the population), as well as exposure to water pollution (80% of the population) and air pollution (55% of the population). The findings suggest that the coordinated strategies are vital across health, environmental, meteorological, and social sectors, considering climatic variability patterns and population vulnerability determinants.

A systematic review on leptospirosis in cattle: A European perspective

Leptospirosis is a zoonotic disease which is globally distributed and represents a classic One Health issue that demands a comprehensive understanding of the hosts, transmission paths, and risk factors of transmission. Bovine leptospirosis often results in economic losses through its severe impact on reproduction performance while it threatens human health at human-cattle-environment interfaces. However, a clear analysis of the disease characteristics in European cattle is currently lacking. The objective of this review was to summarise the current knowledge on the epidemiology of bovine leptospirosis in Europe. We conducted a systematic literature review, screening four electronic databases, and filtered articles published between 2001 and 2021, in English, German, and French. Sixty-two articles were ultimately included in the review. The seroprevalence of leptospirosis in cattle was remarkably variable among studies, probably reflecting local variations but also heterogeneity in the study designs, laboratory methods, and sample sizes. Risk factors positively associated with the disease were diverse, related to local, environmental, and climatic parameters as well as farming practices. The most reported circulating Leptospira serogroups in European cattle were Sejroe (58.5%), Australis (41.5%), Grippotyphosa (41.5%), Icterohaemorrhagiae (37.7%), and Pomona (26.4%), which have also been associated with human infections worldwide. Abortion (58.6%) and fertility disorders (24.1%) were the most frequently reported signs of leptospirosis in European cattle and were generally associated with chronic infections. This work highlights several research gaps, including a lack of harmonisation in diagnostic methods, a lack of large-scale studies, and a lack of molecular investigations. Given that predictions regarding the climatic suitability for leptospirosis in Europe suggest an increase of leptospirosis risk it is important to raise awareness among stakeholders and motivate an integrated One Health approach to the prevention and control of this zoonotic disease in cattle and humans.

Range Dynamics of Striped Field Mouse (Apodemus agrarius) in Northern Eurasia under Global Climate Change Based on Ensemble Species Distribution Models

The striped field mouse (Apodemus agrarius Pallas, 1771) is a widespread species in Northern Eurasia. It damages crops and carries zoonotic pathogens. Its current and future range expansion under climate change may negatively affect public health and the economy, warranting further research to understand the ecological and invasive characteristics of the species. In our study, we used seven algorithms (GLM, GAM, GBS, FDA, RF, ANN, and MaxEnt) to develop robust ensemble species distribution models (eSDMs) under current (1970-2000) and future climate conditions derived from global circulation models (GCMs) for 2021-2040, 2041-2060, 2061-2080, and 2081-2100. Simulation of climate change included high-, medium-, and low-sensitivity GCMs under four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). We analyzed the habitat suitability across GCMs and scenarios by constructing geographical ranges and calculating their centroids. The results showed that the range changes depended on both the sensitivity of GCMs and scenario. The main trends were range expansion to the northeast and partial loss of habitat in the steppe area. The striped field mouse may form a continuous range from Central Europe to East Asia, closing the range gap that has existed for 12 thousand years. We present 49 eSDMs for the current and future distribution of A. agrarius (for 2000-2100) with quantitative metrics (gain, loss, change) of the range dynamics under global climate change. The most important predictor variables determining eSDMs are mean annual temperature, mean diurnal range of temperatures, the highest temperature of the warmest month, annual precipitation, and precipitation in the coldest month. These findings could help limit the population of the striped field mouse and predict distribution of the species under global climate change.

Effects of temperature on incidence of bacillary dysentery in a temperate continental arid climate city in northwest China

The effect of ambient temperature on health continues to draw more and more attention with the global warming. Bacillary dysentery (BD) is a major global environmental health issue and affected by temperature and other environmental variables. In the current study, we evaluated the effect of temperature on the incidence of BD from January 1st, 2008 to December 31st, 2011 in Jiayuguan, a temperate continental arid climate city in the Hexi Corridor of northwest China. A distributed lag non-linear model (DLNM) was performed to evaluate the lag effect of temperature on BD up to 30 days. Results showed the risk of BD increased with temperature significantly, especially after 8 °C. The maximum risk of BD was observed at extreme high temperature (29 °C). The effect of temperature on BD risk was significantly divided into short-term effect at lag 5 days and long-term effect at lag 30 days. Age ≤ 15 years were most affected by high temperature. The maximum cumulative risk for lag 30 days (25.8, 95% CIs: 11.8-50.1) was observed at 29 °C. Age ≤ 15 years and females showed short-term effect at lag 5 days and long-term effect at lag 30 days, while age > 15 years and males showed acute short-term effect at lag 0 and light long-term effect at lag 16 days.

A molecular understanding of alphavirus entry and antibody protection

Alphaviruses are arthropod-transmitted RNA viruses that cause epidemics of human infection and disease on a global scale. These viruses are classified as either arthritogenic or encephalitic based on their genetic relatedness and the clinical syndromes they cause. Although there are currently no approved therapeutics or vaccines against alphaviruses, passive transfer of monoclonal antibodies confers protection in animal models. This Review highlights recent advances in our understanding of the host factors required for alphavirus entry, the mechanisms of action by which protective antibodies inhibit different steps in the alphavirus infection cycle and candidate alphavirus vaccines currently under clinical evaluation that focus on humoral immunity. A comprehensive understanding of alphavirus entry and antibody-mediated protection may inform the development of new classes of countermeasures for these emerging viruses.

Current Risk of Dirofilariosis Transmission in the Iberian Peninsula (Spain and Portugal) and the Balearic Islands (Spain) and Its Future Projection under Climate Change Scenarios

Dirofilariosis is a vector-borne zoonotic disease whose distribution is linked to the presence of culicid mosquitoes. Spain and Portugal are considered endemic countries; however, the distribution of dirofilariosis is not uniform. Our aim was to develop a more accurate risk model of dirofilariosis transmission for the Iberian Peninsula (Spain and Portugal) and the Balearic Islands (Spain). To do this, we used a set of key variables related to parasite transmission: the potential distribution of suitable habitats for Culex pipiens calculated via an ecological niche model (ENM) and the potential number of Dirofilaria spp. generations. The resulting model was validated with the prevalence and geolocation of D. immitis-infected dogs from all provinces and districts. In addition, the impact of possible future climatic conditions was estimated. A quantitative estimate of the risk of infection by Dirofilaria spp. was obtained at a resolution of 1 km². The entire analyzed territory was susceptible to contact with the parasite. The highest risk of infection was found throughout the eastern coastal strip and the south of the Iberian Peninsula and the Balearic Islands, as well as in the areas surrounding the basins of the main rivers, and the lowest risk was located in the higher-altitude areas. We found a robust and positive relationship between the risk of dirofilariosis and the observed prevalence of infested dogs in the study area (β ± SE = 3.32 ± 1.43 p < 0.05). In 2080, the percentage of territory gain for Cx. pipiens will increase to 49.98%, which will increase the risk of infection. This new model provides a high predictive value for the current and predicted presence and risk and can serve as a tool for the management and control of dirofilariosis.

Climate change and communicable diseases in the Gulf Cooperation Council (GCC) countries

A review of the extant literature reveals the extent to which the spread of communicable diseases will be significantly impacted by climate change. Specific research into how this will likely be observed in the countries of the Gulf Cooperation Council (GCC) is, however, greatly lacking. This report summarises the unique public health challenges faced by the GCC countries in the coming century, and outlines the need for greater investment in public health research and disease surveillance to better forecast the imminent epidemiological landscape. Significant data gaps currently exist regarding vector occurrence, spatial climate measures, and communicable disease case counts in the GCC - presenting an immediate research priority for the region. We outline policy work necessary to strengthen public health interventions, and to facilitate evidence-driven mitigation strategies. Such research will require a transdisciplinary approach, utilising existing cross-border public health initiatives, to ensure that such investigations are well-targeted and effectively communicated.

Climate Change and Travel: Harmonizing to Abate Impact

Purpose of Review

With climate change being the single biggest health threat facing humanity, this review aims to identify the climate-sensitive health risks to the traveler and to recognize the role that travel plays in contributing to the detrimental effects of climate change. With this understanding, adaptations for transformational action can be made.

Recent Findings

Travel and tourism, including transportation, food consumption, and accommodation, is responsible for a large percentage of the world’s carbon emissions which is contributing to the climate change crisis at an alarming rate. Climate change is a health emergency that is resulting in a rise of significant health impacts to the traveler including increased heat illnesses; food-, water-, and vector-borne diseases; and increasing risk of exposure to emerging infectious diseases. Patterns of future travel and destination choices are likely to change due to climactic factors such as temperature and extreme weather events, forced migration, degradation, and disappearance of popular and natural tourist destinations.

Summary

Global warming is and will continue to alter the landscape of travel medicine with expansion of transmission seasons and geographic ranges of disease, increased risk of infections and harmful marine toxins, and introduction of emerging infections to naïve populations. This will have implications for pre-travel counseling in assessing risk and discussing the environmental influences on travel. Travelers and stakeholders should be engaged in a dialogue to understand their “climate footprint,” to innovate sustainable solutions, and be empowered to make immediate, conscientious, and responsible choices to abate the impact of breaching critical temperature thresholds.

Comprehensive Dynamic Influence of Multiple Meteorological Factors on the Detection Rate of Bacterial Foodborne Diseases under Spatio-Temporal Heterogeneity

Foodborne diseases are a critical public health problem worldwide and significantly impact human health, economic losses, and social dynamics. Understanding the dynamic relationship between the detection rate of bacterial foodborne diseases and a variety of meteorological factors is crucial for predicting outbreaks of bacterial foodborne diseases. This study analyzed the spatio-temporal patterns of vibriosis in Zhejiang Province from 2014 to 2018 at regional and weekly scales, investigating the dynamic effects of various meteorological factors. Vibriosis had a significant temporal and spatial pattern of aggregation, and a high incidence period occurred in the summer seasons from June to August. The detection rate of Vibrio parahaemolyticus in foodborne diseases was relatively high in the eastern coastal areas and northwestern Zhejiang Plain. Meteorological factors had lagging effects on the detection rate of V. parahaemolyticus (3 weeks for temperature, 8 weeks for relative humidity, 8 weeks for precipitation, and 2 weeks for sunlight hours), and the lag period varied in different spatial agglomeration regions. Therefore, disease control departments should launch vibriosis prevention and response programs that are two to eight weeks in advance of the current climate characteristics at different spatio-temporal clustering regions.

Multisectoral Perspectives on Global Warming and Vector-borne Diseases: a Focus on Southern Europe

Purpose of Review

The climate change (CC) or global warming (GW) modifies environment that favors vectors' abundance, growth, and reproduction, and consequently, the rate of development of pathogens within the vectors. This review highlights the threats of GW-induced vector-borne diseases (VBDs) in Southern Europe (SE) and the need for mitigation efforts to prevent potential global health catastrophe.

Recent Findings

Reports showed astronomical surges in the incidences of CC-induced VBDs in the SE. The recently (2022) reported first cases of African swine fever in Northern Italy and West Nile fever in SE are linked to the CC-modified environmental conditions that support vectors and pathogens' growth and development, and disease transmission.

Summary

VBDs endemic to the tropics are increasingly becoming a major health challenge in the SE, a temperate region, due to the favorable environmental conditions caused by CC/GW that support vectors and pathogens' biology in the previously non-endemic temperate regions.

How Antimicrobial Resistance Is Linked to Climate Change: An Overview of Two Intertwined Global Challenges

Globally, antimicrobial resistance (AMR) and climate change (CC) are two of the top health emergencies, and can be considered as two interlinked public health priorities. The complex commonalities between AMR and CC should be deeply investigated in a One Health perspective. Here, we provided an overview of the current knowledge about the relationship between AMR and CC. Overall, the studies included pointed out the need for applying a systemic approach to planetary health. Firstly, CC increasingly brings humans and animals into contact, leading to outbreaks of zoonotic and vector-borne diseases with pandemic potential. Although it is well-established that antimicrobial use in human, animal and environmental sectors is one of the main drivers of AMR, the COVID-19 pandemic is exacerbating the current scenario, by influencing the use of antibiotics, personal protective equipment, and biocides. This also results in higher concentrations of contaminants (e.g., microplastics) in natural water bodies, which cannot be completely removed from wastewater treatment plants, and which could sustain the AMR spread. Our overview underlined the lack of studies on the direct relationship between AMR and CC, and encouraged further research to investigate the multiple aspects involved, and its effect on human health.

The influence of climate change on food production and food safety

Food security and food safety are two concepts related to food risks. The majority of studies regarding climate change and food risks are related to the security of food provision. The objective of this study was to review the current state of knowledge of the influence of climate change on food production and food safety. The literature search was carried out by specifying each area individually (crops, ranching, fishing, food safety, etc.), including the term "climate change" and other specific factors such as CO₂, ozone, biotoxins, mortality, heat, etc.) The increase in carbon dioxide concentrations together with the increase in global temperatures theoretically produces greater yields in crops destined for human and animal consumption. However, the majority of studies have shown that crop yields are decreasing, due to the increase in the frequency of extreme weather events. Furthermore, these climate anomalies are irregularly distributed, with a greater impact on developing countries that have a lower capacity to address climate change. All of these factors result in greater uncertainty in terms of food provision and market speculation. An increase in average temperatures could lead to an increased risk of proliferation of micro-organisms that produce food-borne illnesses, such as salmonella and campylobacter. However, in developed countries with information systems that document the occurrence of these diseases over time, no clear trend has been determined, in part because of extensive food conservation controls.

Does climate change transform military medicine and defense medical support?

Background

Climate change has effects on multiple aspects of human life, such as access to food and water, expansion of endemic diseases as well as an increase of natural disasters and related diseases. The objective of this review is to summarize the current knowledge on climate change effects on military occupational health, military healthcare in a deployed setting, and defense medical logistics.

Methods

Online databases and registers were searched on August 22^nd, 2022 and 348 papers retrieved, published between 2000 and 2022, from which we selected 8 publications that described climate effects on military health. Papers were clustered according to a modified theoretical framework for climate change effects on health, and relevant items from each paper were summarized.

Results

During the last decades a growing body of climate change related publications was identified, which report that climate change has a significant impact on human physiology, mental health, water- and vector borne infectious diseases, as well as air pollution. However, regarding the specific climate effects on military health the level of evidence is low. The effects on defense medical logistics include vulnerabilities in the cold supply chain, in medical devices functioning, in need for air conditioning, and in fresh water supply.

Conclusions

Climate change may transform both the theoretical framework and practical implementations in military medicine and military healthcare systems. There are significant knowledge gaps on climate change effects on the health of military personnel in operations of both combat and non-combat nature, alerting the need for prevention and mitigation of climate-related health issues. Further research within the fields of disaster and military medicine is needed to explore this novel field. As climate effects on humans and the medical supply chain may degrade military capability, significant investments in military medical research and development are needed.

Application of logistic differential equation models for early warning of infectious diseases in Jilin Province

Background

There is still a relatively serious disease burden of infectious diseases and the warning time for different infectious diseases before implementation of interventions is important. The logistic differential equation models can be used for predicting early warning of infectious diseases. The aim of this study is to compare the disease fitting effects of the logistic differential equation (LDE) model and the generalized logistic differential equation (GLDE) model for the first time using data on multiple infectious diseases in Jilin Province and to calculate the early warning signals for different types of infectious diseases using these two models in Jilin Province to solve the disease early warning schedule for Jilin Province throughout the year.

Methods

Collecting the incidence of 22 infectious diseases in Jilin Province, China. The LDE and GLDE models were used to calculate the recommended warning week (RWW), the epidemic acceleration week (EAW) and warning removed week (WRW) for acute infectious diseases with seasonality, respectively.

Results

Five diseases were selected for analysis based on screening principles: hemorrhagic fever with renal syndrome (HFRS), shigellosis, mumps, Hand, foot and mouth disease (HFMD), and scarlet fever. The GLDE model fitted the above diseases better (0.80 ≤ R2 ≤ 0.94, P <  0. 005) than the LDE model. The estimated warning durations (per year) of the LDE model for the above diseases were: weeks 12–23 and 40–50; weeks 20–36; weeks 15–24 and 43–52; weeks 26–34; and weeks 16–25 and 41–50. While the durations of early warning (per year) estimated by the GLDE model were: weeks 7–24 and 36–51; weeks 13–37; weeks 11–26 and 39–54; weeks 23–35; and weeks 12–26 and 40–50.

Conclusions

Compared to the LDE model, the GLDE model provides a better fit to the actual disease incidence data. The RWW appeared to be earlier when estimated with the GLDE model than the LDE model. In addition, the WRW estimated with the GLDE model were more lagged and had a longer warning time.

[Environmentally friendly absorption of anesthetic gases : First experiences with a commercial anesthetic gas capture system]

Anesthetic gases are potent greenhouse gases, which are currently released into the atmosphere where they remain for many years. Strategies to reduce the carbon footprint in anesthesiology without compromising patient safety are urgently needed. Since 2020 several departments of anesthesiology have installed anesthetic gas capture systems with which anesthetic gases can be collected. This article aims to describe the anesthetic gas capture system CONTRAfluran™ and to give an overview of the first experiences in four departments of anesthesiology working with the new device in the daily clinical routine. The CONTRAfluran™ system presents a new concept in the surgical setting that has the potential to reduce the carbon footprint in anesthesiology; however, in order to accurately estimate CO₂ equivalent savings, more information concerning the reprocessing and data on the pharmacokinetics of anesthetic gases are needed. Application of the CONTRAfluran™ system in daily clinical routine is feasible when anesthesiologists are aware of specific issues. In order to minimize the carbon footprint, it remains essential to implement the specific recommendations in the position paper of the German Society of Anaesthesiology and Intensive Care medicine (DGAI) and the Professional Association of German Anaesthesiologists (BDA) on ecological sustainability in anesthesiology and intensive care medicine and to support further research.

Climate Change and Health in Urban Areas with a Mediterranean Climate: A Conceptual Framework with a Social and Climate Justice Approach

The consequences of climate change are becoming increasingly evident and highlight the important interdependence between the well-being of people and ecosystems. Although climate change is a global phenomenon, its causes and consequences vary dramatically across territories and population groups. Among settings particularly susceptible to health impacts from climate change are cities with a Mediterranean climate. Here, impacts will put additional pressure on already-stressed ecosystems and vulnerable economies and societies, increasing health inequalities. Therefore, this article presents and discusses a conceptual framework for understanding the complex relationship between climate change and health in the context of cities with Mediterranean climate from a social and climate justice approach. The different elements that integrate the conceptual framework are: (1) the determinants of climate change; (2) its environmental and social consequences; (3) its direct and indirect impacts on health; and (4) the role of mitigation and adaptation policies. The model places special emphasis on the associated social and health inequalities through (1) the recognition of the role of systems of privilege and oppression; (2) the distinction between structural and intermediate determinants of climate change at the root of health inequalities; (3) the role of individual and collective vulnerability in mediating the effects of climate change on health; and (4) the need to act from a climate justice perspective to reverse health inequities.

Spatiotemporal dynamics of Escherichia coli presence and magnitude across a national groundwater monitoring network, Republic of Ireland, 2011-2020

Groundwater is a vital drinking water resource and its protection from microbiological contamination is paramount to safeguard public health. The Republic of Ireland (RoI) is characterised by the highest incidence of verocytotoxigenic Escherichia coli (VTEC) enteritis in the European Union (EU), linked to high reliance on unregulated groundwater sources (~16% of the population). Yet, the spatio-temporal factors influencing the frequency and magnitude of microbial contamination remain largely unknown, with past studies typically constrained to spatio-temporally 'limited' sampling campaigns. Accordingly, the current investigation sought to analyse an extensive spatially distributed time-series (2011-2020) of groundwater monitoring data in the RoI. The dataset, compiled by the Environmental Protection Agency (EPA), showed 'high' contamination rates, with 66.7% (88/132) of supplies testing positive for E. coli, and 29.5% (39/132) exceeding concentrations of 10MPN/100 ml (i.e. gross contamination) at least once during the 10-year monitoring period. Seasonal decomposition analyses indicate that E. coli detection rates peak during late autumn/early winter, coinciding with increases in annual rainfall, while gross contamination peaks in spring (May) and late-summer (August), likely reflecting seasonal shifts in agricultural practices. Mixed effects logistic regression modelling indicates that monitoring sources located in karst limestone are statistically associated with E. coli presence (OR = 2.76, p = 0.03) and gross contamination (OR = 2.54, p = 0.037) when compared to poorly productive aquifers (i.e., transmissivity below 10m²/d). Moreover, 5-day and 30-day antecedent rainfall increased the likelihood of E. coli contamination (OR = 1.027, p < 0.001 and OR = 1.005, p = 0.016, respectively), with the former also being associated with gross contamination (OR = 1.042, p < 0.001). As such, it is inferred that preferential flow and direct ingress of surface runoff are the most likely ingress mechanisms associated with E. coli groundwater supply contamination. The results presented are expected to inform policy change around groundwater source protection and provide insight for the development of groundwater monitoring programmes in geologically heterogeneous regions.

Epidemiological characteristics of severe fever with thrombocytopenia syndrome and its relationship with meteorological factors in Liaoning Province, China

Background

Severe fever with thrombocytopenia syndrome (SFTS), one kind of tick-borne acute infectious disease, is caused by a novel bunyavirus. The relationship between meteorological factors and infectious diseases is a hot topic of current research. Liaoning Province has reported a high incidence of SFTS in recent years. However, the epidemiological characteristics of SFTS and its relationship with meteorological factors in the province remain largely unexplored.

Methods

Data on reported SFTS cases were collected from 2011 to 2019. Epidemiological characteristics of SFTS were analyzed. Spearman’s correlation test and generalized linear models (GLM) were used to identify the relationship between meteorological factors and the number of SFTS cases.

Results

From 2011 to 2019, the incidence showed an overall upward trend in Liaoning Province, with the highest incidence in 2019 (0.35/100,000). The incidence was slightly higher in males (55.9%, 438/783), and there were more SFTS patients in the 60–69 age group (31.29%, 245/783). Dalian City and Dandong City had the largest number of cases of SFTS (87.99%, 689/783). The median duration from the date of illness onset to the date of diagnosis was 8 days [interquartile range (IQR): 4–13 days]. Spearman correlation analysis and GLM showed that the number of SFTS cases was positively correlated with monthly average rainfall (r_s = 0.750, P < 0.001; β = 0.285, P < 0.001), monthly average relative humidity (r_s = 0.683, P < 0.001; β = 0.096, P < 0.001), monthly average temperature (r_s = 0.822, P < 0.001; β = 0.154, P < 0.001), and monthly average ground temperature (r_s = 0.810, P < 0.001; β = 0.134, P < 0.001), while negatively correlated with monthly average air pressure (r_s = −0.728, P < 0.001; β = −0.145, P < 0.001), and monthly average wind speed (r_s = −0.272, P < 0.05; β = −1.048, P < 0.001). By comparing both correlation coefficients and regression coefficients between the number of SFTS cases (dependent variable) and meteorological factors (independent variables), no significant differences were observed when considering immediate cases and cases with lags of 1 to 5 weeks for dependent variables. Based on the forward and backward stepwise GLM regression, the monthly average air pressure, monthly average temperature, monthly average wind speed, and time sequence were selected as relevant influences on the number of SFTS cases.

Conclusion

The annual incidence of SFTS increased year on year in Liaoning Province. Incidence of SFTS was affected by several meteorological factors, including monthly average air pressure, monthly average temperature, and monthly average wind speed.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-022-05395-4.

Predicting Incidence of Hepatitis E Using Machine Learning in Jiangsu Province, China

Hepatitis E is an increasingly serious worldwide public health problem that has attracted extensive attention. It is necessary to accurately predict the incidence of hepatitis E to better plan ahead for future medical care. In this study, we developed a Bi-LSTM model that incorporated meteorological factors to predict the prevalence of hepatitis E. The hepatitis E data used in this study are collected from January 2005 to March 2017 by Jiangsu Provincial Center for Disease Control and Prevention. ARIMA, GBDT, SVM, LSTM and Bi-LSTM models are adopted in this study. The data from January 2009 to September 2014 are used as the training set to fit models, and data from October 2014 to March 2017 are used as the testing set to evaluate the predicting accuracy of different models. Selecting models and evaluating the effectiveness of the models are based on mean absolute per cent error (MAPE), root mean square error (RMSE) and mean absolute error (MAE). A total of 44 923 cases of hepatitis E are detected in Jiangsu Province from January 2005 to March 2017. The average monthly incidence rate is 0.35 per 100 000 persons in Jiangsu Province. Incorporating meteorological factors of temperature, water vapour pressure, and rainfall as a combination into the Bi-LSTM Model achieved the state-of-the-art performance in predicting the monthly incidence of hepatitis E, in which RMSE is 0.044, MAPE is 11.88%, and MAE is 0.0377. The Bi-LSTM model with the meteorological factors of temperature, water vapour pressure, and rainfall can fully extract the linear and non-linear information in the hepatitis E incidence data, and has significantly improved the interpretability, learning ability, generalisability and prediction accuracy.

Climate Change Influences on the Potential Distribution of the Sand Fly Phlebotomus sergenti, Vector of Leishmania tropica in Morocco

BACKGROUND

Leishmaniases are a vector-borne disease, re-emerging in several regions of the world posing a burden on public health. As other vector-borne diseases, climate change is a crucial factor affecting the evolution of leishmaniasis. In Morocco, anthroponotic cutaneous leishmaniasis (ACL) is widespread geographically as many foci across the country, mainly in central Morocco. The objective of this study is to evaluate the potential impacts of climate change on the distribution of ACL due to Leishmania tropica, and its corresponding vector Phlebotomus sergenti in Morocco.

METHODS

Using Ecological Niche Modeling (ENM) tool, the estimated geographical range shift of L. tropica and P. sergenti by 2050 was projected under two Representative's Concentration's Pathways (RCPs) to be 2.6 and RCP 8.5 respectively. P. sergenti records were obtained from field collections of the laboratory team and previously published entomological observations, while, epidemiological data for L. tropica were obtained from Moroccan Ministry of Health reports.

RESULTS

Our models under present-day conditions indicated a probable expansion for L. tropica as well as for its vector in Morocco, P. sergenti. It showed a concentrated distribution in the west-central and northern area of Morocco. Future predictions anticipate expansion into areas not identified as suitable for P. sergenti under present conditions, particularly in northern and southeastern areas of Morocco. L. tropica is also expected to have high expansion in southern areas for the next 30 years in Morocco.

CONCLUSION

This indicates that L. tropica and P. sergenti will continue to find suitable climate conditions in the future. A higher abundance of P. sergenti may indeed result in a higher transmission risk of ACL. This information is essential in developing a control plan for ACL in Morocco. However, future investigations on L. tropica reservoirs are needed to confirm our predictions.

Dairy Cattle Density and Temporal Patterns of Human Campylobacteriosis and Cryptosporidiosis in New Zealand

Public health risks associated with the intensification of dairy farming are an emerging concern. Dairy cattle are a reservoir for a number of pathogens that can cause human illness. This study examined the spatial distribution of dairy cattle density and explored temporal patterns of human campylobacteriosis and cryptosporidiosis notifications in New Zealand from 1997 to 2015. Maps of dairy cattle density were produced, and temporal patterns of disease rates were assessed for urban versus rural areas and for areas with different dairy cattle densities using descriptive temporal analyses. Campylobacteriosis and cryptosporidiosis rates displayed strong seasonal patterns, with highest rates in spring in rural areas and, for campylobacteriosis, summer in urban areas. Increases in rural cases often preceded increases in urban cases. Furthermore, disease rates in areas with higher dairy cattle densities tended to peak before areas with low densities or no dairy cattle. Infected dairy calves may be a direct or indirect source of campylobacteriosis or cryptosporidiosis infection in humans through environmental or occupational exposure routes, including contact with animals or feces, recreational contact with contaminated waterways, and consumption of untreated drinking water. These results have public health implications for populations living, working, or recreating in proximity to dairy farms.

Climate Changes Exacerbate the Spread of Ixodes ricinus and the Occurrence of Lyme Borreliosis and Tick-Borne Encephalitis in Europe-How Climate Models Are Used as a Risk Assessment Approach for Tick-Borne Diseases

Climate change has influenced the transmission of a wide range of vector-borne diseases in Europe, which is a pressing public health challenge for the coming decades. Numerous theories have been developed in order to explain how tick-borne diseases are associated with climate change. These theories include higher proliferation rates, extended transmission season, changes in ecological balances, and climate-related migration of vectors, reservoir hosts, or human populations. Changes of the epidemiological pattern have potentially catastrophic consequences, resulting in increasing prevalence of tick-borne diseases. Thus, investigation of the relationship between climate change and tick-borne diseases is critical. In this regard, climate models that predict the ticks’ geographical distribution changes can be used as a predicting tool. The aim of this review is to provide the current evidence regarding the contribution of the climatic changes to Lyme borreliosis (LB) disease and tick-borne encephalitis (TBE) and to present how computational models will advance our understanding of the relationship between climate change and tick-borne diseases in Europe.

A Perspective towards Multi-Hazard Resilient Systems: Natural Hazards and Pandemics

The concept of resilience has been used extensively across the sciences in engineering and the humanities. It is applied to ecology, medicine, economics, and psychology. The novel coronavirus disease (COVID-19) has posed an extraordinary challenge to the resilience of healthcare systems, communities, and nations and has profoundly altered our previous day-to-day operations. This paper presents a discussion of the definitions and characteristics of resilient systems. Scenarios are utilized to qualitatively explore key relationships, responses, and paths for recovery across different system types. The purpose is to develop an integrated approach that can accommodate simultaneous threats to system resilience, in particular, impacts from a natural hazard in conjunction with COVID-19. This manuscript is the first to advocate for more in-depth and quantitative research utilizing transdisciplinary approaches that can accommodate considerations across our built environment and healthcare system infrastructures in pursuit of designing systems that are resilient to both natural hazards and pandemic impacts.

Norovirus Genogroup II Epidemics and the Potential Effect of Climate Change on Norovirus Transmission in Taiwan

The activity of norovirus varies from season to season, and the effect of climate change on the incidence of norovirus outbreaks is a widely recognized yet poorly understood phenomenon. Investigation of the possible association between climatic factors and the incidence of norovirus is key to a better understanding of the epidemiology of norovirus and early prediction of norovirus outbreaks. In this study, clinical stool samples from acute gastroenteritis outbreaks were collected from January 2015 to June 2019 in Taiwan. Data analysis from our study indicated that more than half of the cases were reported in the winter and spring seasons, including those caused by norovirus of genotypes GII (genogroup II).2, GII.3, GII.6, and GII.17, and 45.1% of the patients who tested positive for norovirus were infected by the GII.4 norovirus in autumn. However, GII.6 norovirus accounted for a higher proportion of the cases reported in summer than any other strain. Temperature is a crucial factor influencing patterns of epidemic outbreaks caused by distinct genotypes of norovirus. The results of this study may help experts predict and issue early public warnings of norovirus transmission and understand the effect of climate change on norovirus outbreaks caused by different genotypes and occurring in different locations.

Climate change accelerates winter transmission of a zoonotic pathogen

Many zoonotic diseases are weather sensitive, raising concern how their distribution and outbreaks will be affected by climate change. At northern high latitudes, the effect of global warming on especially winter conditions is strong. By using long term monitoring data (1980-1986 and 2003-2013) from Northern Europe on temperature, precipitation, an endemic zoonotic pathogen (Puumala orthohantavirus, PUUV) and its reservoir host (the bank vole, Myodes glareolus), we show that early winters have become increasingly wet, with a knock-on effect on pathogen transmission in its reservoir host population. Further, our study is the first to show a climate change effect on an endemic northern zoonosis, that is not induced by increased host abundance or distribution, demonstrating that climate change can also alter transmission intensity within host populations. Our results suggest that rainy early winters accelerate PUUV transmission in bank voles in winter, likely increasing the human zoonotic risk in the North.

Association among sentinel surveillance, meteorological factors, and infectious disease in Gwangju, Korea

The outbreak of new infectious diseases is threatening human survival. Transmission of such diseases is determined by several factors, with climate being a very important factor. This study was conducted to assess the correlation between the occurrence of infectious diseases and climatic factors using data from the Sentinel Surveillance System and meteorological data from Gwangju, Jeollanam-do, Republic of Korea. The climate of Gwangju from June to September is humid, with this city having the highest average temperature, whereas that from December to February is cold and dry. Infection rates of Salmonella (temperature: r = 0.710**; relative humidity: r = 0.669**), E. coli (r = 0.617**; r = 0.626**), rotavirus (r =  - 0.408**; r =  - 0.618**), norovirus (r =  - 0.463**; r =  - 0.316**), influenza virus (r =  - 0.726**; r =  - 0.672**), coronavirus (r =  - 0.684**; r =  - 0.408**), and coxsackievirus (r = 0.654**; r = 0.548**) have been shown to have a high correlation with seasonal changes, specifically in these meteorological factors. Pathogens showing distinct seasonality in the occurrence of infection were observed, and there was a high correlation with the climate characteristics of Gwangju. In particular, viral diseases show strong seasonality, and further research on this matter is needed. Due to the current COVID-19 pandemic, quarantine and prevention have become important to block the spread of infectious diseases. For this purpose, studies that predict infectivity through various types of data related to infection are important.

The evolving story of Borrelia burgdorferi sensu lato transmission in Europe

Beside mosquitoes, ticks are well-known vectors of different human pathogens. In the Northern Hemisphere, Lyme borreliosis (Eurasia, LB) or Lyme disease (North America, LD) is the most commonly occurring vector-borne infectious disease caused by bacteria of the genus Borrelia which are transmitted by hard ticks of the genus Ixodes. The reported incidence of LB in Europe is about 22.6 cases per 100,000 inhabitants annually with a broad range depending on the geographical area analyzed. However, the epidemiological data are largely incomplete, because LB is not notifiable in all European countries. Furthermore, not only differ reporting procedures between countries, there is also variation in case definitions and diagnostic procedures. Lyme borreliosis is caused by several species of the Borrelia (B.) burgdorferi sensu lato (s.l.) complex which are maintained in complex networks including ixodid ticks and different reservoir hosts. Vector and host influence each other and are affected by multiple factors including climate that have a major impact on their habitats and ecology. To classify factors that influence the risk of transmission of B. burgdorferi s.l. to their different vertebrate hosts as well as to humans, we briefly summarize the current knowledge about the pathogens including their astonishing ability to overcome various host immune responses, regarding the main vector in Europe Ixodes ricinus, and the disease caused by borreliae. The research shows, that a higher standardization of case definition, diagnostic procedures, and standardized, long-term surveillance systems across Europe is necessary to improve clinical and epidemiological data.

The emergence of Dirofilaria repens in a non-endemic area influenced by climate change: dynamics of transmission using a mathematical model

Dirofilaria repens is a nematode affecting domestic and wild canids, transmitted by several species of mosquitoes of different genera. It usually causes a non-pathogenic subcutaneous infection in dogs and is the principal agent of human dirofilariasis in the Old World. The geographic distribution of D. repens is changing rapidly, and several factors contribute to the spread of the infection to non-endemic areas. A mathematical model for transmission of Dirofilaria spp. was built, using a system of ordinary differential equations that consider the interactions between reservoirs, vectors, and humans. The transmission simulations of D. repens were carried out considering a projection in time, with intervals of 15 and 100 years. For the dynamics of the vector, seasonal variations were presented as series with quarter periodicity during the year. The results of the simulations highlight the peak of contagions in the reservoir and in humans, a product of the action of the vector when it remains active throughout the year. A 300% infection increase in the reservoir was observed during the first decade and remains present in the population with a representative number of cases. When the vector maintains its density and infectivity during the year, the incidence of the infection in humans increases. Accumulated cases amount to 45 per 100,000 inhabitants, which corresponds to a cumulative incidence of 0.05%, in 85 years. This indicates that early prevention of infection in canids would significantly reduce the disease, also reducing the number of accumulated cases of human dirofilariasis by D. repens. The interaction between the simulations generated by the model highlights the sensitivity of the epidemiological curve to the periodicity of seasonality, reaffirming the hypothesis of the probability of movement of the zoonotic disease to non-endemic areas, due to climate change.

The Effects of Lifestyle on the Risk of Lyme Disease in the United States: Evaluation of Market Segmentation Systems in Prevention and Control Strategies

The aim of this study was to investigate lifestyles at risk of Lyme disease, and to geographically identify target populations/households at risk based on their lifestyle preferences. When coupled with geographically identified patient health information (e.g., incidence, diagnostics), lifestyle data provide a more solid base of information for directing public health objectives in minimizing the risk of Lyme disease and targeting populations with Lyme-disease-associated lifestyles. We used an ESRI Tapestry segmentation system that classifies U.S. neighborhoods into 67 unique segments based on their demographic and socioeconomic characteristics. These 67 segments are grouped within 14 larger "LifeModes" that have commonalities based on lifestyle and life stage. Our dataset contains variables denoting the dominant Tapestry segments within each U.S. county, along with annual Lyme disease incidence rates from 2000 through 2017, and the average incidence over these 18 years. K-means clustering was used to cluster counties based on yearly incidence rates for the years 2000-2017. We used analysis of variance (ANOVA) statistical testing to determine the association between Lyme disease incidence and LifeModes. We further determined that the LifeModes Affluent Estates, Upscale Avenues, GenXurban, and Cozy Country Living were associated with higher Lyme disease risk based on the results of analysis of means (ANOM) and Tukey's post hoc test, indicating that one of these LifeModes is the LifeMode with the greatest Lyme disease incidence rate. We further conducted trait analysis of the high-risk LifeModes to see which traits were related to higher Lyme disease incidence. Due to the extreme regional nature of Lyme disease incidence, we carried out our national-level analysis at the regional level. Significant differences were detected in incidence rates and LifeModes in individual regions. We mapped Lyme disease incidence with associated LifeModes in the Northeast, Southeast, Midcontinent, Rocky Mountain, and Southwest regions to reflect the location-dependent nature of the relationship between lifestyle and Lyme disease.

Spatial modeling of mortality from acute lower respiratory infections in children under 5 years of age in 2000-2017: a global study

BACKGROUND

Over the past few decades, various goals have been defined to reduce the mortality of children caused by acute lower respiratory infections (ALRIs) worldwide. However, few spatial studies to date have reported on ALRI deaths.

PURPOSE

We aimed to assess the spatial modeling of mortality from ALRI in children under 5 years of age during 2000-2017 using a global data.

METHODS

The data on the mortality of children under 5 years old caused by ALRI were initially obtained from the official website of the World Health Organization. The income status of their home countries was also gathered from the Country Income Groups (World Bank Classification) website and divided into 5 categories. After that, in the ArcGIS 10.6 environment, a database was created and the statistical tests and related maps were extracted. The Global Moran's I statistic, Getis-Ord Gi statistic, and geographically weighted regression were used for the analyses. In this study, higher z scores indicated the hot spots, while lower z scores indicated the cold spots.

RESULTS

In 2000-2017, child mortality showed a downward trend from 17.6 per 100,000 children to 8.1 and had a clustered pattern. Hot spots were concentrated in Asia in 2000 but shifted toward African countries by 2017. A cold spot that formed in Europe in 2007 showed an ascending trend by 2017. Based on the results of geographically weighted regression test, the regions identified as the hot spots of mortality from ALRI in children under 5 years old were among the middle-income countries (R2=0.01, adjusted R2=8.77).

CONCLUSION

While the total number of child deaths in 2000-2017 has decreased, the number of hot spots has increased among countries. This study also concluded that, during the study period, Central and Western Africa countries became the main new hot spots of deaths from ALRI.

A one health glossary to support communication and information exchange between the human health, animal health and food safety sectors

Collaboration across sectors, disciplines and countries is a key concept to achieve the overarching One Health (OH) objective for better human, animal and environmental health. Differences in terminology and interpretation of terms are still a significant hurdle for cross-sectoral information exchange and collaboration within the area of OH including One Health Surveillance (OHS). The development of the here described glossary is a collaborative effort of three projects funded within the One Health European Joint Programme (OHEJP). We describe the infrastructure of the OHEJP Glossary, as well as the methodology to create such a cross-sectoral web resource in a collaborative manner. The new OHEJP Glossary allows OH actors to identify terms with different or shared interpretation across sectors. Being aware of such differences in terminology will help overcome communication hurdles in the future and consequently support collaboration and a more inclusive development of OHS. The OHEJP Glossary was implemented as a web-based, user-friendly and searchable infrastructure that complies with the Findable, Accessible, Interoperable, Reusable (FAIR) data principles. Maintenance, enrichment and quality control of the OHEJP Glossary is supported through a flexible and updatable curation infrastructure. This increases the uptake potential and exploitation of the OHEJP Glossary by other OH initiatives or tools and services.

Climate anomalies and childhood growth in Peru

Climate change has been linked to poor childhood growth and development through maternal stress, nutritional insults related to lean harvests, and exposure to infectious diseases. Vulnerable populations are often most susceptible to these stressors. This study tested whether susceptibility to linear growth faltering is higher among Peruvian children from indigenous, rural, low-education, and low-income households. High-resolution weather and household survey data from Demographic and Health Survey 1996-2012 were used to explore height-for-age z-scores (HAZ) at each year of life from 0 to 5. Rural, indigenous children at age 0-1 experience a HAZ reduction of 0.35 units associated with prenatal excess rainfall which is also observed at age 4-5. Urban, non-indigenous children at age 4-5 experience a HAZ increase of 0.07 units associated with postnatal excess rainfall, but this advantage is not seen among rural, indigenous children. These findings highlight the need to consider developmental stage and social predictors as key components in public health interventions targeting increased climate change resilience.

Review of fractional epidemic models

The global impact of corona virus (COVID-19) has been profound, and the public health threat it represents is the most serious seen in a respiratory virus since the 1918 influenza A(H1N1) pandemic. In this paper, we have focused on reviewing the results of epidemiological modelling especially the fractional epidemic model and summarized different types of fractional epidemic models including fractional Susceptible-Infective-Recovered (SIR), Susceptible-Exposed-Infective-Recovered (SEIR), Susceptible-Exposed-Infective-Asymptomatic-Recovered (SEIAR) models and so on. Furthermore, we propose a general fractional SEIAR model in the case of single-term and multi-term fractional differential equations. A feasible and reliable parameter estimation method based on modified hybrid Nelder-Mead simplex search and particle swarm optimisation is also presented to fit the real data using fractional SEIAR model. The effective methods to solve the fractional epidemic models we introduced construct a simple and effective analytical technique that can be easily extended and applied to other fractional models, and can help guide the concerned bodies in preventing or controlling, even predicting the infectious disease outbreaks.

[New challenges for intensive care medicine due to climate change and global warming]

Hintergrund

In den letzten 5 Dekaden wird ein kontinuierlicher Anstieg der globalen mittleren Temperatur registriert; darüber hinaus häufen sich Naturkatastrophen (z. B. schwere Stürme, Überflutungen, Dürren und großflächige Brände). Die Auswirkungen von globaler Erderwärmung und Klimawandel auf die Gesundheit betreffen die Zunahme von respiratorischen, kardiovaskulären, renalen und kognitiv-psychischen Erkrankungen. Des Weiteren lässt sich auch in Europa eine Veränderung der Häufigkeit und des Musters von Infektionskrankheiten beobachten.

Material und Methoden

In diesem Beitrag werden die wesentlichen Studien präsentiert, die sich mit klimawandelassoziierten Erkrankungen befassen, mit besonderem Blick auf solche Erkrankungen, die eine Herausforderung für die Intensivmedizin darstellen.

Ergebnisse

Aktuelle epidemiologische Daten und statistische Extrapolationen legen nahe, dass Erkrankungen im Gefolge des Klimawandels (akute infektionsbedingte respiratorische und intestinale Erkrankungen, Exazerbationen bei vorbestehender Lungenschädigung, hitzebedingte Dehydratation, zerebrale Insulte und Myokardinfarkte) für die Intensivmedizin von Relevanz sind. Ein besonderes Augenmerk liegt auf einer signifikanten Zunahme von akuten Nierenschädigungen während Hitzewellen. Ein bisher nichtgekanntes „Muster“ der Infektionskrankheiten erfordert neue Kenntnisse und gezieltes Management. In einigen Studien wurden nach Hitzewellen und Naturkatastrophen anhaltende psychische Beeinträchtigungen der Betroffenen, z. B. posttraumatische Belastungsstörungen, registriert.

Schlussfolgerungen

Die Intensivmedizin muss sich den Herausforderungen durch globale Erderwärmung und Klimawandel stellen. Sowohl langsame, aber kontinuierliche (Anstieg der Temperatur) als auch akute Veränderungen (Hitzewellen, Naturkatastrophen) werden den steigenden Bedarf intensivmedizinischer Leistungen (z. B. auch eine steigende Nachfrage nach Nierenersatzverfahren) induzieren. Intensivmediziner werden sich mit der Diagnostik und dem Management von klimawandelassoziierten Erkrankungen beschäftigen müssen. Eine Initiative der betroffenen Fachgesellschaften ist begrüßenswert.

Dynamics of a stochastic delayed avian influenza model with mutation and temporary immunity

In this paper, the dynamic behaviors are studied for a stochastic delayed avian influenza model with mutation and temporary immunity. First, we prove the existence and uniqueness of the global positive solution for the stochastic model. Second, we give two different thresholds [Formula: see text] and [Formula: see text], and further establish the sufficient conditions of extinction and persistence in the mean for the avian-only subsystem and avian-human system, respectively. Compared with the corresponding deterministic model, the thresholds affected by the white noises are smaller than the ones of the deterministic system. Finally, numerical simulations are carried out to support our theoretical results. It is concluded that the vaccination immunity period can suppress the spread of avian influenza during poultry and human populations, while prompt the spread of mutant avian influenza in human population.

Extreme weather events and dengue outbreaks in Guangzhou, China: a time-series quasi-binomial distributed lag non-linear model

Dengue transmission is climate-sensitive and permissive conditions regularly cause large outbreaks in Asia-Pacific area. As climate change progresses, extreme weather events such as heatwaves and unusually high rainfall are predicted more intense and frequent, but their impacts on dengue outbreaks remain unclear so far. This paper aimed to investigate the relationship between extreme weather events (i.e., heatwaves, extremely high rainfall and extremely high humidity) and dengue outbreaks in China. We obtained daily number of locally acquired dengue cases and weather factors for Guangzhou, China, for the period 2006-2015. The definition of dengue outbreaks was based on daily number of locally acquired cases above the threshold (i.e., mean + 2SD of daily distribution of dengue cases during peaking period). Heatwave was defined as ≥2 days with temperature ≥ 95th percentile, and extreme rainfall and humidity defined as daily values ≥95th percentile during 2006-2015. A generalized additive model was used to examine the associations between extreme weather events and dengue outbreaks. Results showed that all three extreme weather events were associated with increased risk of dengue outbreaks, with a risk increase of 115-251% around 6 weeks after heatwaves, 173-258% around 6-13 weeks after extremely high rainfall, and 572-587% around 6-13 weeks after extremely high humidity. Each extreme weather event also had good capacity in predicting dengue outbreaks, with the model's sensitivity, specificity, accuracy, and area under the receiver operating characteristics curve all exceeding 86%. This study found that heatwaves, extremely high rainfall, and extremely high humidity could act as potential drivers of dengue outbreaks.