Lassa fever is a longstanding public health concern in West Africa. Recent molecular studies have confirmed the fundamental role of the rodent host (Mastomys natalensis) in driving human infections, but control and prevention efforts remain hampered by a limited baseline understanding of the disease’s true incidence, geographical distribution and underlying drivers. Here, we show that Lassa fever occurrence and incidence is influenced by climate, poverty, agriculture and urbanisation factors. However, heterogeneous reporting processes and diagnostic laboratory access also appear to be important drivers of the patchy distribution of observed disease incidence. Using spatiotemporal predictive models we show that including climatic variability added retrospective predictive value over a baseline model (11% decrease in out-of-sample predictive error). However, predictions for 2020 show that a climate-driven model performs similarly overall to the baseline model. Overall, with ongoing improvements in surveillance there may be potential for forecasting Lassa fever incidence to inform health planning.
BACKGROUND: Floods have affected 2.3 billion people worldwide in the last 20 years, and are associated with a wide range of negative health outcomes. Climate change is projected to increase the number of people exposed to floods due to more variable precipitation and rising sea levels. Vulnerability to floods is highly dependent on economic wellbeing and other societal factors. Therefore, this systematic review synthesizes the evidence on health effects of flood exposure among the population of sub-Saharan Africa. METHODS: We systematically searched two databases, Web of Science and PubMed, to find published articles. We included studies that (1) were published in English from 2010 onwards, (2) presented associations between flood exposure and health indicators, (3) focused on sub-Saharan Africa, and (4) relied on a controlled study design, such as cohort studies, case-control studies, cross-sectional studies, or quasi-experimental approaches with a suitable comparator, for instance individuals who were not exposed to or affected by floods or individuals prior to experiencing a flood. RESULTS: Out of 2306 screened records, ten studies met our eligibility criteria. We included studies that reported the impact of floods on water-borne diseases (n = 1), vector-borne diseases (n = 8) and zoonotic diseases (n = 1). Five of the ten studies assessed the connection between flood exposure and malaria. One of these five evaluated the impact of flood exposure on malaria co-infections. The five non-malaria studies focused on cholera, scabies, taeniasis, Rhodesian sleeping sickness, alphaviruses and flaviviruses. Nine of the ten studies reported significant increases in disease susceptibility after flood exposure. CONCLUSION: The majority of included studies of the aftermath of floods pointed to an increased risk of infection with cholera, scabies, taeniasis, Rhodesian sleeping sickness, malaria, alphaviruses and flaviviruses. However, long-term health effects, specifically on mental health, non-communicable diseases and pregnancy, remain understudied. Further research is urgently needed to improve our understanding of the health risks associated with floods, which will inform public policies to prevent and reduce flood-related health risks.
BACKGROUND & OBJECTIVES: Issues such as emerging and re-emerging infectious diseases, antimicrobial resistance, food security, biosafety and biosecurity are associated with changes in land use, population growth, urbanization, global travel and trade and climate change. As a result, a trans-disciplinary approach among human, animal and environmental health disciplines gained support. The Indian Council of Medical Research (ICMR) and Indian Council of Agricultural Research (ICAR) decided to establish a National Institute of One Health at Nagpur, Maharashtra, India. In this context, two collaborative research projects, funded by the ICAR and ICMR were initiated to conduct the epidemiological surveillance of selected zoonotic diseases in Central India. METHODS: Disease surveillance and molecular detection employing standard techniques like enzyme linked immunosorbent assay (ELISA), immuno-fluroscent assay (IFA), standard tube agglutination test (STAT) , Rose Bengal plate test (RBPT) and polymerase chain reaction (PCR) were undertaken based on the disease to be screened. RESULTS: In animals, the seropositivities for listeriosis (7.66%) and brucellosis (11.69%) were recorded. The occurrence of tuberculosis (3.8%) and leptospirosis (6.33%) was detected by PCR. Through cross-sectional studies from suspected human population with associated risk factors for zoonotic diseases, the seropositivity of brucellosis (1.83-11%), listeriosis (1.01-10.18 %), leptospirosis (8.14-12.67%) and scrub typhus (1.78-20.34%) was recorded. The investigations on scrub typhus indicated bimodal pattern during the months of pre-monsoon and post-monsoon season with a peak in post-monsoon in human cases. Ornithonyssus bacoti mites were identified from the rodents as a vector harbouring Orientia tsutsugamushi. The bovine tuberculosis was detected in 1.43 per cent human cases employing molecular assay. INTERPRETATION & CONCLUSIONS: The data indicated the occurrence of important zoonotic diseases adversely affecting the livestock health and human wellbeing. The scientific collaboration between veterinary and medical faculties has set an example for effective implementation of One Health (OH) programme for the establishment of National Institute of OH.
Lessons learned from recent pandemics, such as SARS-CoV-2 have illustrated that education and training in a One Health approach, which recognizes the interdependency of the health of people, animals and the environment, are essential in improving preparations for and responses to disease outbreaks. For this reason and others, there is a critical need to provide One Health (OH) training to medical professionals early in their careers. 133 U.S. medical schools were surveyed for the incorporation of OH learning activities. Results showed that 56% of surveyed programs included OH-related subject matter, primarily in the context of preclinical classroom learning. This supports previous findings that OH education efforts in medical schools lag behind veterinary schools, with many veterinary schools already including OH as a central part of their curricula. A two week OH elective course for third year medical students was developed and implemented at Georgetown University School of Medicine. Topics such as emerging infectious diseases, zoonoses, vector-borne diseases, epidemiology, emergency preparedness, the human-animal bond, and effects of climate change on public health were discussed. The 21 participants were surveyed before and after the course regarding their knowledge and understanding of OH. Participation in the course enhanced the students’ knowledge of OH and furthermore, the students’ perception of the importance of incorporating OH within the curriculum and in their future careers changed significantly. This study provides clear evidence that successful integration of OH material is achievable at low cost through interdepartmental and interdisciplinary collaboration. A more holistic approach to health care that takes into consideration environmental, wildlife, and domestic animal factors, and introduction of concepts such as OH into the medical school curriculum, can help close the educational gaps identified in the surveys.
PURPOSE: This paper examines whether the usage of the concept of One Health in Canada-based research aligns with traditional Indigenous notions of health and wellness. METHODS: A comprehensive search of the literature was conducted using primary databases, including Scholars Portal, ProQuest Social Science, Sociological Abstracts (ProQuest), OVID Healthstar, Embase, Medline, Pubmed and Google Scholar. Papers discussing One Health and Indigenous Health were selected and analyzed through Nvivo12 to generate common themes across the studies. RESULTS: The analysis identified three major themes that focused on One Health as it relates to climate change, zoonosis, and social relationships between humans and animals. Climate change was seen to have affected the environmental health of Northern latitude areas where many Indigenous communities reside. Infectious diseases within Indigenous communities were a frequent topic of study and indicated that infections transmitted by dogs are likely to be addressed with One Health interventions. One Health interventions are likely to equally address the health of humans, animals, and the environment. CONCLUSIONS: No significant connection between One Health and Indigenous knowledges was established in the analyzed articles. Articles discussed One Health as it pertains to epidemiological surveillance and research. The implications of utilizing One Health towards Indigenous Peoples and culture were not explicitly addressed.
Recognition of climate-sensitive infectious diseases is crucial for mitigating health threats from climate change. Recent studies have reasoned about potential climate sensitivity of diseases in the Northern/Arctic Region, where climate change is particularly pronounced. By linking disease and climate data for this region, we here comprehensively quantify empirical climate-disease relationships. Results show significant relationships of borreliosis, leptospirosis, tick-borne encephalitis (TBE), Puumala virus infection, cryptosporidiosis, and Q fever with climate variables related to temperature and freshwater conditions. These data-driven results are consistent with previous reasoning-based propositions of climate-sensitive infections as increasing threats for humans, with notable exceptions for TBE and leptospirosis. For the latter, the data imply decrease with increasing temperature and precipitation experienced in, and projected for, the Northern/Arctic Region. This study provides significant data-based underpinning for simplified empirical assessments of the risks of several infectious diseases under future climate change.
As the nation’s public health leader, the Centers for Disease Control and Prevention (CDC) is actively engaged in a national effort to protect the public’s health from the harmful effects of climate change. Scientists from CDC’s National Center for Emerging and Zoonotic Infectious Diseases (NCEZID) are at the forefront of many of these efforts. This report highlights some of that work and also looks ahead to the important work yet to come. Lyme disease, West Nile virus disease, and Valley fever. These are just some of the infectious diseases that are on the rise and spreading to new areas of the United States. Milder winters, warmer summers, and fewer days of frost make it easier for these and other infectious diseases to expand into new geographic areas and infect more people. To understand climate change’s impact, it’s important to look at some of the common ways these diseases spread—through mosquito and tick bites, contact with animals, fungi, and water.
The role of climate driving zoonotic diseases’ population dynamics has typically been addressed via retrospective analyses of national aggregated incidence records. A central question in epidemiology has been whether seasonal and interannual cycles are driven by climate variation or generated by socioeconomic factors. Here, we use compartmental models to quantify the role of rainfall and temperature in the dynamics of snakebite, which is one of the primary neglected tropical diseases. We took advantage of space-time datasets of snakebite incidence, rainfall, and temperature for Colombia and combined it with stochastic compartmental models and iterated filtering methods to show the role of rainfall-driven seasonality modulating the encounter frequency with venomous snakes. Then we identified six zones with different rainfall patterns to demonstrate that the relationship between rainfall and snakebite incidence was heterogeneous in space. We show that rainfall only drives snakebite incidence in regions with marked dry seasons, where rainfall becomes the limiting resource, while temperature does not modulate snakebite incidence. In addition, the encounter frequency differs between regions, and it is higher in regions where Bothrops atrox can be found. Our results show how the heterogeneous spatial distribution of snakebite risk seasonality in the country may be related to important traits of venomous snakes’ natural history.
Fascioliasis is a worldwide emerging snail-borne zoonotic trematodiasis with a great spreading capacity linked to animal and human movements, climate change, and anthropogenic modifications of freshwater environments. South America is the continent with more human endemic areas caused by Fasciola hepatica, mainly in high altitude areas of Andean regions. The Peruvian Cajamarca area presents the highest human prevalences reported, only lower than those in the Bolivian Altiplano. Sequencing of the complete rDNA ITS-2 allowed for the specific and haplotype classification of lymnaeid snails collected in seasonal field surveys along a transect including 2007-3473 m altitudes. The species Galba truncatula (one haplotype preferentially in higher altitudes) and Pseudosuccinea columella (one haplotype in an isolated population), and the non-transmitting species Lymnaea schirazensis (two haplotypes mainly in lower altitudes) were found. Climatic seasonality proved to influence G. truncatula populations in temporarily dried habitats, whereas L. schirazensis appeared to be more climatologically independent due to its extreme amphibious ecology. Along the southeastern transect from Cajamarca city, G. truncatula and L. schirazensis shared the same site in 7 localities (46.7% of the water collections studied). The detection of G. truncatula in 11 new foci (73.3%), predominantly in northern localities closer to the city, demonstrate that the Cajamarca transmission risk area is markedly wider than previously considered. Lymnaea schirazensis progressively increases its presence when moving away from the city. Results highlight the usefulness of lymnaeid surveys to assess borders of the endemic area and inner distribution of transmission foci. Similar lymnaeid surveys are still in need to be performed in the wide northern and western zones of the Cajamarca city. The coexistence of more than one lymnaeid transmitting species, together with a morphologically indistinguishable non-transmitting species and livestock movements inside the area, conform a complex scenario which poses difficulties for the needed One Health control intervention.
A debate has emerged over the potential socio-ecological drivers of wildlife-origin zoonotic disease outbreaks and emerging infectious disease (EID) events. This Review explores the extent to which the incidence of wildlife-origin infectious disease outbreaks, which are likely to include devastating pandemics like HIV/AIDS and COVID-19, may be linked to excessive and increasing rates of tropical deforestation for agricultural food production and wild meat hunting and trade, which are further related to contemporary ecological crises such as global warming and mass species extinction. Here we explore a set of precautionary responses to wildlife-origin zoonosis threat, including: (a) limiting human encroachment into tropical wildlands by promoting a global transition to diets low in livestock source foods; (b) containing tropical wild meat hunting and trade by curbing urban wild meat demand, while securing access for indigenous people and local communities in remote subsistence areas; and (c) improving biosecurity and other strategies to break zoonosis transmission pathways at the wildlife-human interface and along animal source food supply chains.
Zoonotic disease outbreaks are an important threat to human health and numerous drivers have been recognized as contributing to their increasing frequency. Identifying and quantifying relationships between drivers of zoonotic disease outbreaks and outbreak severity is critical to developing targeted zoonotic disease surveillance and outbreak prevention strategies. However, quantitative studies of outbreak drivers on a global scale are lacking. Attributes of countries such as press freedom, surveillance capabilities and latitude also bias global outbreak data. To illustrate these issues, we review the characteristics of the 100 largest outbreaks in a global dataset (n = 4463 bacterial and viral zoonotic outbreaks), and compare them with 200 randomly chosen background controls. Large outbreaks tended to have more drivers than background outbreaks and were related to large-scale environmental and demographic factors such as changes in vector abundance, human population density, unusual weather conditions and water contamination. Pathogens of large outbreaks were more likely to be viral and vector-borne than background outbreaks. Overall, our case study shows that the characteristics of large zoonotic outbreaks with thousands to millions of cases differ consistently from those of more typical outbreaks. We also discuss the limitations of our work, hoping to pave the way for more comprehensive future studies. This article is part of the theme issue ‘Infectious disease macroecology: parasite diversity and dynamics across the globe’.
At least 10,000 virus species have the ability to infect humans but, at present, the vast majority are circulating silently in wild mammals(1,2). However, changes in climate and land use will lead to opportunities for viral sharing among previously geographically isolated species of wildlife(3,4). In some cases, this will facilitate zoonotic spillover-a mechanistic link between global environmental change and disease emergence. Here we simulate potential hotspots of future viral sharing, using a phylogeographical model of the mammal-virus network, and projections of geographical range shifts for 3,139 mammal species under climate-change and land-use scenarios for the year 2070. We predict that species will aggregate in new combinations at high elevations, in biodiversity hotspots, and in areas of high human population density in Asia and Africa, causing the cross-species transmission of their associated viruses an estimated 4,000 times. Owing to their unique dispersal ability, bats account for the majority of novel viral sharing and are likely to share viruses along evolutionary pathways that will facilitate future emergence in humans. Notably, we find that this ecological transition may already be underway, and holding warming under 2 °C within the twenty-first century will not reduce future viral sharing. Our findings highlight an urgent need to pair viral surveillance and discovery efforts with biodiversity surveys tracking the range shifts of species, especially in tropical regions that contain the most zoonoses and are experiencing rapid warming.
Every year we see many changes in the world around us. One of these changes is the climate and weather, and it could be one of the reasons for changing behaviors between humans and animals, which could cause zoonotic diseases. We usually face new diseases that infect a growing population leading to a pandemic. Different reasons are leading to an increase in the emergence of new infections. Some of these diseases can be associated with zoonotic diseases and the diverse world of viral genetics and its failures. Furthermore, properties like mutations and also unknown effects of these mutations on the virulence of the agents make it challenging to trace new diseases. As we know, preventing emerging diseases is inevitable and viral diseases are dangerous, and some viruses can spread quickly and cause an endemic or pandemic. As was noticed during the recent pandemic, the need to study emerging diseases in the field of virology has become more and more apparent to us. In this review, we want to look at how we could monitor and control these diseases with new approaches and what should be done when a disease emerges. Moreover, we will investigate risk factors, ways to deal with emerging viral infections, new treatments that make the condition better when a person gets infected, and the future of these diseases. We will also study the ways to deal with pandemics with the new generations of vaccines.
OBJECTIVE: To describe and quantify the extent of wildlife and environment sector inclusion in country evaluation and prioritization tools for health security, and to provide practical recommendations for global and national action to improve pandemic prevention and preparedness. METHODS: To assess coverage of wildlife and other environmental aspects, we reviewed major health security reports (including World Organisation for Animal Health Performance of Veterinary Services reports, and World Health Organization Joint External Evaluations and follow-on National Action Plans for Health Security) published by 107 countries and territories. We extracted information on stated coverage gaps, wildlife surveillance systems and priority diseases. We also searched National Biodiversity Strategies and Action Plans published by 125 countries to assess whether disease surveillance or prevention activities were included. FINDINGS: We noted that the occurrence frequency of keywords indicative of wildlife, environment, biodiversity and climate factors varied with type of report and between countries. We found that more than half (57.9%, 62/107) of the reporting countries did not provide any evidence of a functional wildlife health surveillance programme. Most countries (83.2%, 89/107) indicated specific gaps in operations, coordination, scope or capacity. Only eight of the 125 countries (6.4%) publishing a National Biodiversity Strategy and Action Plan reported tangible activities related to wildlife health or zoonotic disease. CONCLUSION: Overall, despite their importance for pandemic prevention, wildlife and environmental considerations are neglected in health security priorities and plans. Strengthening wildlife health capacity and operations should be emphasized in One Health efforts to monitor and mitigate known and novel disease risks.
The emergence of an outbreak of Monkeypox disease (MPXD) is caused by a contagious zoonotic Monkeypox virus (MPXV) that has spread globally. Yet, there is no study investigating the effect of climatic changes on MPXV transmission. Thus, studies on the changing epidemiology, evolving nature of the virus, and ecological niche are highly paramount. Determination of the role of potential meteorological drivers including temperature, precipitation, relative humidity, dew point, wind speed, and surface pressure is beneficial to understand the MPXD outbreak. This study examines the changes in MPXV cases over time while assessing the meteorological characteristics that could impact these disparities from the onset of the global outbreak. To conduct this data-based research, several well-accepted statistical techniques including Simple Exponential Smoothing (SES), Auto-Regressive Integrated Moving Average (ARIMA), Automatic forecasting time-series model (Prophet), and Autoregressive Integrated Moving Average with Explanatory Variables (ARIMAX) were applied to delineate the correlation of the meteorological factors on global daily Monkeypox cases. Data on MPXV cases including affected countries spanning from 6 May 2022, to 9 November 2022, from global databases and meteorological data were used to evaluate the developed models. According to the ARIMAX model, the results showed that temperature, relative humidity, and surface pressure have a positive impact [(51.56, 95% confidence interval (CI): -274.55 to 377.68), (17.32, 95% CI: -83.71 to 118.35) and (23.42, 95% CI: -9.90 to 56.75), respectively] on MPXV cases. In addition, dew/frost point, precipitation, and wind speed show a significant negative impact on MPXD cases. The Prophet model showed a significant correlation with rising MPXD cases, although the trend predicts peak values while the overall trend increases. This underscores the importance of immediate and appropriate preventive measures (timely preparedness and proactive control strategies) with utmost priority against MPXD including awareness-raising programs, the discovery, and formulation of effective vaccine candidate(s), prophylaxis and therapeutic regimes, and management strategies.
Recent cases of monkeypox (MPX), a zoonotic illness caused by monkeypox virus (MPXV), outside of Africa have prompted international public health concerns. The emergence, re-emergence, and global dispersion of zoonoses are profoundly impacted by a wide variety of causes, including but not limited to climate change, urbanization, animal migration, quick means of travel and tourism, vector biology, anthropogenic influences, and natural factors. Human MPX was first identified in the Democratic Republic of the Congo (DRC) in 1970, and since then it has spread throughout Africa, particularly to West and Central Africa, with some instances even emerging outside of Africa. Since the 1970s, there has been an increasing trend in the occurrence of human MPX, with the DRC seeing the largest increase. The median age at first presentation has increased from 4 years in the 1970s to 21 years in the current time. The total fatality rate was 8.7%, although there was a significant variation between clades: Central African (10.6%) and West African (3.6%). Since 2003, sporadic outbreaks have occurred outside of Africa due to imports and travel-related dissemination. Risky practices that could lead to contracting MPX include having contact with infected animals or people. There is still much to learn about MPXV, such as the reason for the sudden increase in cases while travel links from endemic countries have not yet been established profoundly, identity the natural reservoir animal(s), make advances in diagnostics, increase surveillance and monitoring, carry out in-depth epidemiological investigations, genome sequencing and phylogenetic analysis, explore the reasons for the changing epidemiology and evolving nature of the virus, its ecological niche, and the discovery of effective treatment and management of MPX. This l mini-review aims to reveal an increase in the number of reported cases of MPX worldwide, with the highest concentration in the DRC, as well as its spread to other countries and a shift in the median age of patients from infants to teenagers and young adults highlighting from older years to current 2022 MPX outbreaks. Some cross-protection against MPX was provided by smallpox vaccination, suggesting that its discontinuation may have contributed to an increase in human-to-human transmission. The disease’s worldwide significance is underscored by the fact that it has spread beyond Africa. As the epidemiology of this resurging disease is constantly shifting, surveillance and detection programs are crucial to keeping up with it.
‘One World – One Health’ is a developing concept which aims to explicitly incorporate linkages between the environment and human society into wildlife and human health care. Past work in the field has concentrated on aspects of disease, particularly emerging zoonoses, and focused on terrestrial systems. Here, we argue that marine environments are crucial components of the ‘One World – One Health’ framework, and that coral reefs are the epitome of its underlying philosophy. That is, they provide vast contributions to a wide range of ecosystem services with strong and direct links to human well-being. Further, the sensitivity of corals to climate change, and the current emergence of a wide range of diseases, make coral reefs ideal study systems to assess links, impacts, and feedback mechanisms that can affect human and ecosystem health. There are well established protocols for monitoring corals, as well as global networks of coral researchers, but there remain substantial challenges to understanding these complex systems, their health and links to provisioning of ecosystem services. We explore these challenges and conclude with a look at how developing technology offers potential ways of addressing them. We argue that a greater integration of coral reef research into the ‘One World – One Health’ framework will enrich our understanding of the many links within, and between, ecosystems and human society. This will ultimately support the development of measures for improving the health of both humans and the environment.
The threats, both real and perceived, surrounding the development of new and emerging infectious diseases of humans are of critical concern to public health and well-being. Among these risks is the potential for zoonotic transmission to humans of species of the malaria parasite, Plasmodium, that have been considered historically to infect exclusively non-human hosts. Recently observed shifts in the mode, transmission, and presentation of malaria among several species studied are evidenced by shared vectors, atypical symptoms, and novel host-seeking behavior. Collectively, these changes indicate the presence of environmental and ecological pressures that are likely to influence the dynamics of these parasite life cycles and physiological make-up. These may be further affected and amplified by such factors as increased urban development and accelerated rate of climate change. In particular, the extended host-seeking behavior of what were once considered non-human malaria species indicates the specialist niche of human malaria parasites is not a limiting factor that drives the success of blood-borne parasites. While zoonotic transmission of non-human malaria parasites is generally considered to not be possible for the vast majority of Plasmodium species, failure to consider the feasibility of its occurrence may lead to the emergence of a potentially life-threatening blood-borne disease of humans. Here, we argue that recent trends in behavior among what were hitherto considered to be non-human malaria parasites to infect humans call for a cross-disciplinary, ecologically-focused approach to understanding the complexities of the vertebrate host/mosquito vector/malaria parasite triangular relationship. This highlights a pressing need to conduct a multi-species investigation for which we recommend the construction of a database to determine ecological differences among all known Plasmodium species, vectors, and hosts. Closing this knowledge gap may help to inform alternative means of malaria prevention and control.
The Covid-19 pandemic is of zoonotic origin, and many other emerging infections of humans have their origin in an animal host population. We review the challenges involved in modelling the dynamics of wildlife-human interfaces governing infectious disease emergence and spread. We argue that we need a better understanding of the dynamic nature of such interfaces, the underpinning diversity of pathogens and host-pathogen association networks, and the scales and frequencies at which environmental conditions enable spillover and host shifting from animals to humans to occur. The major drivers of the emergence of zoonoses are anthropogenic, including the global change in climate and land use. These, and other ecological processes pose challenges that must be overcome to counterbalance pandemic risk. The development of more detailed and nuanced models will provide better tools for analysing and understanding infectious disease emergence and spread.
Climate change can have a complex impact that also influences human and animal health. For example, climate change alters the conditions for pathogens and vectors of zoonotic diseases. Signs of this are the increasing spread of the West Nile and Usutu viruses and the establishment of new vector species, such as specific mosquito and tick species, in Europe and other parts of the world. With these changes come new challenges for maintaining human and animal health. This paper reports on an analysis of the literature focused on a bibliometric analysis of the Scopus database and VOSviewer software for creating visualization maps which identifies the zoonotic health risks for humans and animals caused by climate change. The sources retained for the analysis totaled 428 and different thresholds (N) were established for each item varying from N 5 to 10. The main findings are as follows: First, published documents increased in 2009-2015 peaking in 2020. Second, the primary sources have changed since 2018, partly attributable to the increase in human health concerns due to human-to-human transmission. Third, the USA, the UK, Canada, Australia, Italy, and Germany perform most zoonosis research. For instance, sixty documents and only 17 countries analyzed for co-authorship analysis met the threshold led by the USA; the top four author keywords were “climate change”, “zoonosis”, “epidemiology”, and “one health;” the USA, the UK, Germany, and Spain led the link strength (inter-collaboration); the author keywords showed that 37 out of the 1023 keywords met the threshold, and the authors’ keyword’s largest node of the bibliometric map contains the following: infectious diseases, emerging diseases, disease ecology, one health, surveillance, transmission, and wildlife. Finally, zoonotic diseases, which were documented in the literature in the past, have evolved, especially during the years 2010-2015, as evidenced by the sharp augmentation of publications addressing ad-hoc events and peaking in 2020 with the COVID-19 outbreak.
Emerging infectious diseases (EIDs), especially those with zoonotic potential, are a growing threat to global health, economy, and safety. The influence of global warming and geoclimatic variations on zoonotic disease epidemiology is evident by alterations in the host, vector, and pathogen dynamics and their interactions. The objective of this article is to review the current literature on the observed impacts of climate change on zoonoses and discuss future trends. We evaluated several climate models to assess the projections of various zoonoses driven by the predicted climate variations. Many climate projections revealed potential geographical expansion and the severity of vector-borne, waterborne, foodborne, rodent-borne, and airborne zoonoses. However, there are still some knowledge gaps, and further research needs to be conducted to fully understand the magnitude and consequences of some of these changes. Certainly, by understanding the impact of climate change on zoonosis emergence and distribution, we could better plan for climate mitigation and climate adaptation strategies.
Species are shifting their distributions in response to climate change. This geographic reshuffling may result in novel co-occurrences among species, which could lead to unseen biotic interactions, including the exchange of parasites between previously isolated hosts. Identifying potential new host-parasite interactions would improve forecasting of disease emergence and inform proactive disease surveillance. However, accurate predictions of future cross-species disease transmission have been hampered by the lack of a generalized approach and data availability. Here, we propose a framework to predict novel host-parasite interactions based on a combination of niche modelling of future host distributions and parasite sharing models. Using the North American ungulates as a proof of concept, we show this approach has high cross-validation accuracy in over 85% of modelled parasites and find that more than 34% of the host-parasite associations forecasted by our models have already been recorded in the literature. We discuss potential sources of uncertainty and bias that may affect our results and similar forecasting approaches, and propose pathways to generate increasingly accurate predictions. Our results indicate that forecasting parasite sharing in response to shifts in host geographic distributions allow for the identification of regions and taxa most susceptible to emergent pathogens under climate change. This article is part of the theme issue ‘Infectious disease macroecology: parasite diversity and dynamics across the globe’.
Non-technical summaryHumans have the tendency to damage the natural environment in many ways. Deforestation and conversion of forests for residential, industrial development, and expansion of agricultural crops, as well as the burning of fossil fuels, are some activities that disrupt natural ecosystems and wildlife and contribute to climate change. As a result, the life cycles of pathogens and intermediate hosts (insects, rodents, mammals) as well as biodiversity are affected. Through these activities, humans meet wild animals that transmit pathogens, resulting in their infection by zoonoses and causing epidemics-pandemics, the effects of which have as their final recipient himself and his activities. Technical summaryThis article aims to highlight the two-way relationship between those human activities and the occurrence of epidemics-pandemics. We will try to elaborate this two-way relationship, through the overview of the current pandemic (origin of SARS-CoV-2, modes of transmission, clinical picture of the disease of COVID-19, influence of weather and air pollution on prevalence and mortality, pandemic effects, and treatments). They are used as primary sources, scientific articles, literature, websites, and databases (Supplementary appendix) to analyze factors involved in the occurrence and transmission of zoonotic diseases in humans (Ebola, influenza, Lyme disease, dengue fever, cholera, AIDS/HIV, SARS-CoV, MERS-CoV). The present paper concluded that humanity today faces two major challenges: controlling the COVID-19 pandemic and minimizing the risk of a new global health crisis occurring in the future. The first can be achieved through equitable access to vaccines and treatments for all people. The second needs the global community to make a great change and start protecting the natural environment and its ecosystems through the adoption of prevention policies. Summary of social mediaTwo-way relationship between human activities and epidemics highlighted, through review of the COVID-19 pandemic.
BACKGROUND: Cystic and alveolar echinococcosis (CE and AE) are neglected tropical diseases caused by Echinococcus granulosus sensu lato and E. multilocularis, and are emerging zoonoses in Kyrgyzstan. In this country, the spatial distribution of CE and AE surgical incidence in 2014-2016 showed marked heterogeneity across communities, suggesting the presence of ecological determinants underlying CE and AE distributions. METHODOLOGY/PRINCIPAL FINDINGS: For this reason, in this study we assessed potential associations between community-level confirmed primary CE (no.=2359) or AE (no.=546) cases in 2014-2016 in Kyrgyzstan and environmental and climatic variables derived from satellite-remote sensing datasets using conditional autoregressive models. We also mapped CE and AE relative risk. The number of AE cases was negatively associated with 10-year lag mean annual temperature. Although this time lag should not be considered as an exact measurement but with associated uncertainty, it is consistent with the estimated 10-15-year latency following AE infection. No associations were detected for CE. We also identified several communities at risk for CE or AE where no disease cases were reported in the study period. CONCLUSIONS/SIGNIFICANCE: Our findings support the hypothesis that CE is linked to an anthropogenic cycle and is less affected by environmental risk factors compared to AE, which is believed to result from spillover from a wild life cycle. As CE was not affected by factors we investigated, hence control should not have a geographical focus. In contrast, AE risk areas identified in this study without reported AE cases should be targeted for active disease surveillance in humans. This active surveillance would confirm or exclude AE transmission which might not be reported with the present passive surveillance system. These areas should also be targeted for ecological investigations in the animal hosts.
BACKGROUND: Large-scale epidemics of haemorrhagic fever with renal syndrome (HFRS) have been reported mostly in Asia and Europe, with around 100,000 people affected each year. In the Southeast Europe, Balkan region, HFRS is endemic disease with approximately 100 cases per year. Our aim was to describe epidemiological characteristics of HFRS in five Western Balkan (WB) countries and to describe correlation between HFRS incidence and major meteorological event that hit the area in May 2014. METHODS: National surveillance data of HFRS from Bosnia and Herzegovina, Croatia, Montenegro, North Macedonia and Serbia obtained from 1 January 2006 to 31 December 2015 were collected and analysed. RESULTS: In a 10-year period, a total of 1,065 HFRS patients were reported in five WB countries. Cumulative incidence rate ranged from 0.05 to 15.80 per 100.000 inhabitants (in North Macedonia and Montenegro respectively). Increasing number of HFRS cases was reported with a peak incidence in three specific years (2008, 2012, and 2014). Average incidence for the entire area was higher in males than females (5.63 and 1.90 per 100.000 inhabitants respectively). Summer was the season with the highest number of cases and an average incidence rate of 1.74/100.000 inhabitants across 10-year period. Haemorrhagic fever with renal syndrome incidence was significantly increased (7.91/100.000 inhabitants) in 2014, when a few months earlier, severe floods affected several WB countries. A strong significant negative correlation (r = -.84, p < .01) between the monthly incidence of HFRS and the number of months after May's floods was demonstrated for the total area of WB. CONCLUSION: Our findings demonstrate that the HFRS incidence had similar distribution (general, age, sex and seasonality) across majority of the included countries. Summer was the season with the highest recorded incidence. Common epidemic years were detected in all observed countries as well as a negative correlation between the monthly incidence of HFRS and the number of months after May's cyclone.
Zoonoses impart a significant public health burden in Australia particularly in Queensland, a state with increasing environmental stress due to extreme weather events and rapid expansion of agriculture and urban developments. Depending on the organism and the environment, a proportion of zoonotic pathogens may survive from hours to years outside the animal host and contaminate the air, water, food, or inanimate objects facilitating their transmission through the environment (i.e. environmentally transmitted). Although most of these zoonotic infections are asymptomatic, severe cases that require hospitalisation are an important indicator of zoonotic infection risk. To date, no studies have investigated the risk of hospitalisation due to environmentally transmitted zoonotic diseases and its association with proxies of sociodemographic and environmental stress. In this study we analysed hospitalisation data for a group of environmentally transmitted zoonoses during a 15-year period using a Bayesian spatial hierarchical model. The analysis incorporated the longest intercensal-year period of consistent Local Government Area (LGA) boundaries in Queensland (1996-2010). Our results showed an increased risk of environmentally transmitted zoonoses hospitalisation in people in occupations such as animal farming, and hunting and trapping animals in natural habitats. This risk was higher in females, compared to the general population. Spatially, the higher risk was in a discrete set of north-eastern, central and southern LGAs of the state, and a probability of 1.5-fold or more risk was identified in two separate LGA clusters in the northeast and south of the state. The increased risk of environmentally transmitted zoonoses hospitalisations in some LGAs indicates that the morbidity due these diseases can be partly attributed to spatial variations in sociodemographic and occupational risk factors in Queensland. The identified high-risk areas can be prioritised for health support and zoonosis control strategies in Queensland.
BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS), a rodent-borne disease, is a severe public health threat. Previous studies have discovered the influence of meteorological factors on HFRS incidence, while few studies have concentrated on the stratified analysis of delayed effects and interaction effects of meteorological factors on HFRS. OBJECTIVE: Huludao City is a representative area in north China that suffers from HFRS with primary transmission by Rattus norvegicus. This study aimed to evaluate the climate factors of lag, interaction, and stratified effects of meteorological factors on HFRS incidence in Huludao City. METHODS: Our researchers collected meteorological data and epidemiological data of HFRS cases in Huludao City during 2007-2018. First, a distributed lag nonlinear model (DLNM) for a maximum lag of 16 weeks was developed to assess the respective lag effect of temperature, precipitation, and humidity on HFRS incidence. We then constructed a generalized additive model (GAM) to explore the interaction effect between temperature and the other two meteorological factors on HFRS incidence and the stratified effect of meteorological factors. RESULTS: During the study period, 2751 cases of HFRS were reported in Huludao City. The incidence of HFRS showed a seasonal trend and peak times from February to May. Using the median WAT, median WTP, and median WARH as the reference, the results of DLNM showed that extremely high temperature (97.5th percentile of WAT) had significant associations with HFRS at lag week 15 (RR = 1.68, 95% CI: 1.04-2.74) and lag week 16 (RR = 2.80, 95% CI: 1.31-5.95). Under the extremely low temperature (2.5th percentile of WAT), the RRs of HFRS infection were significant at lag week 5 (RR = 1.28, 95% CI: 1.01-1.67) and lag 6 weeks (RR = 1.24, 95% CI: 1.01-1.57). The RRs of relative humidity were statistically significant at lag week 10 (RR = 1.19, 95% CI: 1.00-1.43) and lag week 11 (RR = 1.24, 95% CI: 1.02-1.50) under extremely high relative humidity (97.5th percentile of WARH); however, no statistically significance was observed under extremely low relative humidity (2.5th percentile of WARH). The RRs were significantly high when WAT was -10 degrees Celsius (RR = 1.34, 95% CI: 1.02-1.76), -9 degrees Celsius (1.37, 95% CI: 1.04-1.79), and -8 degrees Celsius (RR = 1.34, 95% CI: 1.03-1.75) at lag week 5 and more than 23 degrees Celsius after 15 weeks. Interaction and stratified analyses showed that the risk of HFRS infection reached its highest when both temperature and precipitation were at a high level. CONCLUSIONS: Our study indicates that meteorological factors, including temperature and humidity, have delayed effects on the occurrence of HFRS in the study area, and the effect of temperature can be modified by humidity and precipitation. Public health professionals should pay more attention to HFRS control when the weather conditions of high temperature with more substantial precipitation and 15 weeks after the temperature is higher than 23 degrees Celsius.
BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS) is endemic in Zhejiang Province, China, while few studies have concentrated on the influence of meteorological factors on HFRS incidence in the area. METHODS: Data on HFRS and meteorological factors from January 1, 2008 to December 31, 2020 in Taizhou City, Zhejiang Province were collected. Multivariate analysis was conducted to the relationship between meteorological factors including minimum temperatures, relative humidity, and cumulative rainfall with HFRS. RESULTS: The HFRS incidence peaked in November and December and it was negatively correlated with average and highest average temperatures. Compared with median of meteorological factors, the relative risks (RR) of weekly average temperature at 12 ℃, weekly highest temperature at 18 ℃relative humidity at 40%, and cumulative rainfall at 240 mm were most significant and RRs were 1.41 (95% CI: 1.09-1.82), 1.32 (95% CI: 1.05-1.66), 2.18 (95% CI: 1.16-4.07), and 1.91 (95% CI: 1.16-2.73), respectively. Average temperature, precipitation, relative humidity had interactions on HFRS and the risk of HFRS occurrence increased with the decrease of average temperature and the increase of precipitation. CONCLUSION: Our study results are indicative of the association of environmental factors with the HFRS incidence, probable recommendation could be use of environmental factors as early warning signals for initiating the control measure and response.
Hemorrhagic fever with renal syndrome (HFRS) is caused by hantavirus (HV) infection, and is prevalent across Europe and Asia (mainly China). The genetic variation and wide host range of the HV family may lead to vaccine failure. In this study, we analyzed the gene sequences of HV isolated from different regions of China in order to trace the molecular evolution of HV and the epidemiological trends of HFRS. A total of 16,6975 HFRS cases and 1,689 HFRS-related deaths were reported from 2004 to 2016, with the average annual incidence rate of 0.9674 per 100,000, 0.0098 per 100,000 mortality rate, and case fatality rate 0.99%. The highest number of cases were detected in 2004 (25,041), and after decreasing to the lowest numbers (8,745) in 2009, showed an incline from 2010. The incidence of HFRS is the highest in spring and winter, and three times as many men are affected as women. In addition, farmers account for the largest proportion of all cases. The main hosts of HV are Rattus norvegicus and Apodemus agrarius, and the SEOV strain is mainly found in R. norvegicus and Niviventer confucianus. Phylogenetic analysis showed that at least 10 HTNV subtypes and 6 SEOV subtypes are endemic to China. We found that the clustering pattern of M genome segments was different from that of the S segments, indicating the possibility of gene recombination across HV strains. The recent increase in the incidence of HFRS may be related to climatic factors, such as temperature, relative humidity and hours of sunshine, as well as biological factors like rodent density, virus load in rodents and genetic variation. The scope of vaccine application should be continuously expanded, and surveillance measures and prevention and control strategies should be improved to reduce HFRS infection in China.
BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS) is a serious public health problem in China. The geographic distribution has went throughout China, among which Zhejiang Province is an important epidemic area. Since 1963, more than 110,000 cases have been reported. METHODS: We collected the meteorological factors and socioeconomic indicators of Zhejiang Province, and constructed the HFRS ecological niche model of Zhejiang Province based on the algorithm of maximum entropy. RESULTS: Model AUC from 2009 to 2018, is 0.806-0.901. The high incidence of epidemics in Zhejiang Province is mainly concentrated in the eastern, western and central regions of Zhejiang Province. The contribution of digital elevation model ranged from 2009 to 2018 from 4.22 to 26.0%. The contribution of average temperature ranges from 6.26 to 19.65%, Gross Domestic Product contribution from 7.53 to 21.25%, and average land surface temperature contribution with the highest being 16.73% in 2011. In addition, the average contribution of DMSP/OLS, 20-8 precipitation and 8-20 precipitation were all in the range of 9%. All-day precipitation increases with the increase of rainfall, and the effect curve peaks at 1,250 mm, then decreases rapidly, and a small peak appears again at 1,500 mm. Average temperature response curve shows an inverted v-shape, where the incidence peaks at 17.8(°)C. The response curve of HFRS for GDP and DMSP/OLS shows a positive correlation. CONCLUSION: The incidence of HFRS in Zhejiang Province peaked in areas where the average temperature was 17.8(°)C, which reminds that in the areas where temperature is suitable, personal protection should be taken when going out as to avoid contact with rodents. The impact of GDP and DMSP/OLS on HFRS is positively correlated. Most cities have good medical conditions, but we should consider whether there are under-diagnosed cases in economically underdeveloped areas.
Hemorrhagic fever with renal syndrome (HFRS), caused by hantavirus, is a serious public health problem in China. Despite intensive countermeasures including Patriotic Health Campaign, rodent control and vaccination in affected areas, HFRS is still a potential public health threat in China, with more than 10,000 new cases per year. Previous epidemiological evidence suggested that meteorological factors could influence HFRS incidence, but the studies were mainly limited to a specific city or region in China. This study aims to evaluate the association between monthly HFRS cases and meteorological change at the country level using a multivariate distributed lag nonlinear model (DLNM) from 2004 to 2018. The results from both univariate and multivariate models showed a non-linear cumulative relative risk relationship between meteorological factors (with a lag of 0-6 months) such as mean temperature (Tmean), precipitation, relative humidity (RH), sunshine hour (SH), wind speed (WS) and HFRS incidence. The risk for HFRS cases increased steeply as the Tmean between - 23 and 14.79 °C, SH between 179.4 and 278.4 h and RH remaining above 69% with 50-95 mm precipitation and 1.70-2.00 m/s WS. In conclusion, meteorological factors such as Tmean and RH showed delayed-effects on the increased risk of HFRS in the study and the lag varies across climate factors. Temperature with a lag of 6 months (RR = 3.05) and precipitation with a lag of 0 months (RR = 2.08) had the greatest impact on the incidence of HFRS.
Hemorrhagic fever with renal syndrome (HFRS), a serious threat to human health, is mainly transmitted by rodents in Eurasia. The risk of disease differs according to sex, age, and occupation. Further, temperature and rainfall have some lagging effects on the occurrence of the disease. The quantitative data for these factors in the Tai’an region of China are still unknown. We used a forest map to calculate the risk of HFRS in different populations and used four different mathematical models to explain the relationship between time factors, meteorological factors, and the disease. The results showed that compared with the whole population, the relative risk in rural medical staff and farmers was 5.05 and 2.00, respectively (p < 0.05). Joinpoint models showed that the number of cases decreased by 33.32% per year from 2005 to 2008 (p < 0.05). The generalized additive model showed that air temperature was positively correlated with disease risk from January to June, and that relative humidity was negatively correlated with risk from July to December. From January to June, with an increase in temperature, after 15 lags, the cumulative risk of disease increased at low temperatures. From July to December, the cumulative risk decreased with an increase in the relative humidity. Rural medical staff, farmers, men, and middle-aged individuals were at a high risk of HFRS. Moreover, air temperature and relative humidity are important factors that affect disease occurrence. These associations show lagged and differing effects according to the season.
Climate variability and anomalies are known drivers of the emergence and outbreaks of infectious diseases. In this study, we investigated the potential association between climate factors and anomalies, including El Niño Southern Oscillation (ENSO) and land surface temperature anomalies, as well as the emergence and spillover events of bat-borne viral diseases in humans and livestock in the Asia-Pacific region and the Arabian Peninsula. Our findings from time series analyses, logistic regression models, and structural equation modelling revealed that the spillover patterns of the Nipah virus in Bangladesh and the Hendra virus in Australia were differently impacted by climate variability and with different time lags. We also used event coincidence analysis to show that the emergence events of most bat-borne viral diseases in the Asia-Pacific region and the Arabian Peninsula were statistically associated with ENSO climate anomalies. Spillover patterns of the Nipah virus in Bangladesh and the Hendra virus in Australia were also significantly associated with these events, although the pattern and co-influence of other climate factors differed. Our results suggest that climate factors and anomalies may create opportunities for virus spillover from bats to livestock and humans. Ongoing climate change and the future intensification of El Niño events will therefore potentially increase the emergence and spillover of bat-borne viral diseases in the Asia-Pacific region and the Arabian Peninsula.
Hemorrhagic fever with renal syndrome (HFRS) continued to affect human health across Eurasia, which complicated by climate change has posed a challenge for the disease prevention measures. Nation-wide surveillance data of HFRS cases were collected during 2008-2020.The seasonality and epidemiological features were presented by combining the HFRS incidence and the endemic types data. Factors potentially involved in affecting incidence and shaping disease seasonality were investigated by generalized additive mixed model, distributed lag nonlinear model and multivariate meta-analysis. A total of 76 cities that reported totally 111,054 cases were analyzed. Three endemic types were determined, among them the Type I cities (Hantaan virus-dominant) were related to higher incidence level, showing one spike every year in Autumn-Winter season; Type II (Seoul virus-dominant) cities were related to lower incidence, showing one spike in Spring, while Type III (Hantaan/Seoul-mixed type) showed dual peaks with incidence lying between. Persistently heavy rainfall had significantly negative influence on HFRS incidence in Hantaan virus-dominant endemic area, while a significantly opposite effect was identified when continuously heavy rainfall induced floods, where temperature and relative humidity affected HFRS incidence via an approximately parabolic or linear manner, however few or no such effects was shown in Seoul virus-dominant endemic areas, which was more vulnerable to temperature variation. Dual seasonal pattern of HFRS was depended on the dominant genotypes of hantavirus, and impact of climate on HFRS was greater in Hantaan virus-dominant endemic areas, than in Seoul virus-dominant areas.
BACKGROUND: Reported monthly scrub typhus (ST) cases in Thailand has an increase in the number of cases during 2009-2014. Humidity is a crucial climatic factor for the survival of chiggers, which is the disease vectors. The present study was to determine the role of humidity in ST occurrence in Thailand and its delayed effect. METHODS: We obtained the climate data from the Department of Meteorology, the disease data from Ministry of Public Health. Negative binomial regression combined with a distributed lag non-linear model (NB-DLNM) was employed to determine the non-linear effects of different types of humidity on the disease. This model controlled overdispersion and confounder, including seasonality, minimum temperature, and cumulative total rainwater. RESULTS: The occurrence of the disease in the 6-year period showed the number of cases gradually increased summer season (Mid-February – Mid-May) and then reached a plateau during the rainy season (Mid-May – Mid-October) and then steep fall after the cold season (Mid-October – Mid-February). The high level (at 70%) of minimum relative humidity (RHmin) was associated with a 33% (RR 1.33, 95% CI 1.13-1.57) significant increase in the number of the disease; a high level (at 14 g/m(3)) of minimum absolute humidity (AHmin) was associated with a 30% (RR 1.30, 95% CI 1.14-1.48); a high level (at 1.4 g/kg) of minimum specific humidity (SHmin) was associated with a 28% (RR 1.28, 95% CI 1.04-1.57). The significant effects of these types of humidity occurred within the past month. CONCLUSION: Humidity played a significant role in enhancing ST cases in Thailand, particularly at a high level and usually occurred within the past month. NB-DLNM had good controlled for the overdispersion and provided the precise estimated relative risk of non-linear associations. Results from this study contributed the evidence to support the Ministry of Public Health on warning system which might be useful for public health intervention and preparation in Thailand.
