Climate change and the transmission of vector-borne diseases: a review

Klimawandel und Kindergesundheit – Ein Aufruf zum Handeln

Der Klimawandel ist eine stille Krise und die größte Bedrohung unserer Zeit. Hitze, Extremwetterereignisse und Luftverschmutzung haben besondere Auswirkungen auf Frühgeburtlichkeit, akute und chronische Atemwegserkrankungen, Allergien und Asthma. Auch die Zunahme infektiöser Erkrankungen sowie eine erhöhte Exposition durch Karzinogene sowie deren Folgen werden beobachtet. Neben der Gefahr des Klimawandels für die somatische, hat die Krise auch Einfluss auf die mentale Gesundheit von Heranwachsenden und aggraviert das soziale Ungleichgewicht, wovon Kinder und Jugendliche in besonderer Weise betroffen sind.

Um die von Wissenschaftler:innen prognostizierten Szenarien abzuwenden, braucht es zum einen ein rasches und umfängliches Agieren der Politik, aber auch ein Neudenken unseres Selbstverständnisses als für Kinder- und Jugendgesundheit Verantwortliche sowie eine grundlegende Neuordnung von Prioritäten. Als Akteur:innen im Gesundheitswesen stehen wir besonders in der Verantwortung, uns für eine gesunde Erde einzusetzen. Dies kann und muss schon heute auf verschiedenen Ebenen, als Ärzt:innen, Wissenschaftler:innen, auf Ebenen der Patient:innenversorgung und der Fachgesellschaften erfolgen, um allen Kindern und Jugendlichen eine lebenswerte Zukunft zu ermöglichen.

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.

A Review on Climate, Air Pollution, and Health in North Africa

PURPOSE OF REVIEW

The aim of this review is to summarize and provide clear insights into studies that evaluate the interaction between air pollution, climate, and health in North Africa.

RECENT FINDINGS

Few studies have estimated the effects of climate and air pollution on health in North Africa. Most of the studies highlighted the evidence of the link between climate and air pollution as driving factors and increased mortality and morbidity as health outcomes. Each North African country prioritized research on a specific health factor. It was observed that the health outcome from each driving factor depends on the studied area and data availability. The latter is a major challenge in the region. As such, more studies should be led in the future to cover more areas in North Africa and when more data are available. Data availability will help to explore the applicability of different tools and techniques new to the region. This review explores studies related to climate and air pollution, and their possible impacts on health in North Africa. On one hand, air quality studies have focused mainly on particulate matter exceedance levels and their long-term exposure impacts, namely, morbidity and mortality. The observed differences between the various studies are mainly due to the used exposure-response function, the studied population, background emissions, and natural emission from the Sahara Desert that characterize the region. On the other hand, climate studies have focused primarily on the impact of heat waves, vector-borne disease, and mental disorders. More than half of these studies have been on leishmaniasis disease. The review revealed unbalanced and insufficient research on health impacts from air pollution episodes and climate extremes across the region.

Charting the evidence for climate change impacts on the global spread of malaria and dengue and adaptive responses: a scoping review of reviews

Background

Climate change is expected to alter the global footprint of many infectious diseases, particularly vector-borne diseases such as malaria and dengue. Knowledge of the range and geographical context of expected climate change impacts on disease transmission and spread, combined with knowledge of effective adaptation strategies and responses, can help to identify gaps and best practices to mitigate future health impacts. To investigate the types of evidence for impacts of climate change on two major mosquito-borne diseases of global health importance, malaria and dengue, and to identify the range of relevant policy responses and adaptation strategies that have been devised, we performed a scoping review of published review literature. Three electronic databases (PubMed, Scopus and Epistemonikos) were systematically searched for relevant published reviews. Inclusion criteria were: reviews with a systematic search, from 2007 to 2020, in English or French, that addressed climate change impacts and/or adaptation strategies related to malaria and/or dengue. Data extracted included: characteristics of the article, type of review, disease(s) of focus, geographic focus, and nature of the evidence. The evidence was summarized to identify and compare regional evidence for climate change impacts and adaptation measures.

Results

A total of 32 reviews met the inclusion criteria. Evidence for the impacts of climate change (including climate variability) on dengue was greatest in the Southeast Asian region, while evidence for the impacts of climate change on malaria was greatest in the African region, particularly in highland areas. Few reviews explicitly addressed the implementation of adaptation strategies to address climate change-driven disease transmission, however suggested strategies included enhanced surveillance, early warning systems, predictive models and enhanced vector control.

Conclusions

There is strong evidence for the impacts of climate change, including climate variability, on the transmission and future spread of malaria and dengue, two of the most globally important vector-borne diseases. Further efforts are needed to develop multi-sectoral climate change adaptation strategies to enhance the capacity and resilience of health systems and communities, especially in regions with predicted climatic suitability for future emergence and re-emergence of malaria and dengue. This scoping review may serve as a useful precursor to inform future systematic reviews of the primary literature.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12992-021-00793-2.

Climate adaptation impacting parasitic infection

The steady and ongoing change in climatic patterns across the globe is triggering a cascade of climate-adaptive phenomena, both genetic and behavioral in parasites, and influencing the host–pathogen–transmission triangle. Parasite and vector traits are now heavily influenced due to increasing temperature that almost dissolved geospatial boundaries and impacted the basic reproductive number of parasites. As consequence, continents unknown to some parasites are experiencing altered distribution and abundance of new and emerging parasites that are developing into a newer epidemiological model. These are posing a burden to healthcare and higher disease prevalence. This calls for multidisciplinary actions focusing on One Health to improve and innovate in areas of detection, reporting, and medical countermeasures to combat the growing threat of parasite emergence owing to climate adaptations for better public health outcomes.

Assessing the Factors of Dengue Transmission in Urban Environments of Pakistan

The rationale of this study is to highlight the significance of relationships of dengue transmission with climate and societal factors for four major cities in Pakistan (i.e., Islamabad, Rawalpindi, Lahore, and Karachi). These cities have been observed to report higher numbers of dengue cases in the last few years, with the highest number of cases reported during 2011. With careful consideration, the relationships of dengue transmission with climate factors, human population density, and traveling in the study areas have been taken into account. Regression model and generalized linear mixed model (GLM) with Markov chain Monte Carlo (MCMC) algorithm are computed to determine the relationships and random effects of different social (human population density, traveling) and climate (minimum-maximum temperatures, and rainfall) factors on dengue transmission. Neural network (NN) with multilayer perceptron algorithm is used to analyze the normalized importance of different covariates relative to dengue transmission. The results show that minimum temperature and rainfall, together with societal factors, significantly affecting the transmission of dengue in the study areas. The magnitude of these relationships is also shown by the results of the neural network. GLM also shows the significant random effects of minimum temperature, rainfall, human population density, and traveling on dengue transmission during the studied years (2009–2018).

Long-term predictors of dengue outbreaks in Bangladesh: A data mining approach

The effects of weather variables on the transmission of vector-borne diseases are complex. Relationships can be non-linear, specific to particular geographic locations, and involve long lag times between predictors and outbreaks of disease. This study expands the geographical and temporal range of previous studies in Bangladesh of the mosquito-transmitted viral infection dengue, a major threat to human public health in tropical and subtropical regions worldwide. The analysis incorporates new compound variables such as anomalous events, running averages, consecutive days of particular weather characteristics, seasonal variables based on the traditional Bangla six-season annual calendar, and lag times of up to one year in predicting either the existence or the magnitude of each dengue epidemic. The study takes a novel, comprehensive data mining approach to show that different variables optimally predict the occurrence and extent of an outbreak. The best predictors of an outbreak are the number of rainy days in the preceding two months and the average daily minimum temperature one month prior to the outbreak, while the best predictor of the number of clinical cases is the average humidity six months prior to the month of outbreak. The magnitude of relationships between humidity 6, 7 and 8 months prior to the outbreak suggests the relationship is multifactorial, not due solely to the cyclical nature of prevailing weather conditions but likely due also to the immunocompetence of human hosts.

Correlates of Climate Variability and Dengue Fever in Two Metropolitan Cities in Bangladesh

Dengue fever is a major public health concern in Bangladesh with increased incidence during monsoon. We aimed to assess the correlation of temperature, humidity, and rainfall on dengue fever in two dengue endemic cities in Bangladesh. It was a time series analysis of climate factors and dengue occurrence data in Dhaka and Chittagong cities from 1 January 2000 to 31 December 2009. Daily mean temperature, rainfall, and humidity data were obtained from the Bangladesh meteorological department and daily dengue cases data were obtained from the directorate general of health services (DGHS) of Bangladesh. The mean dengue incidence was 31.62 (SD 28.7) per 100,000 in Dhaka whereas it was 5.76 (SD 11.7) per 100,000 population in Chittagong. The incidence of dengue cases was found significantly associated with the monthly mean temperature, total rainfall, and mean humidity in Dhaka, though in Chittagong, the significantly associated factors​ ​​​​​​were monthly total rainfall and mean humidity. The autoregressive integrated moving average (ARIMA) model identified monthly mean humidity and total rainfall as the most significant contributing factors for dengue cases in Dhaka and Chittagong, respectively. Our study reinforces the relationship of climate parameters with dengue fever, which will support policy-makers in developing a climate-based early warning system for dengue in Bangladesh.

Climate Variability and Dengue Hemorrhagic Fever in Hanoi, Viet Nam, During 2008 to 2015

Dengue fever/dengue hemorrhagic fever (DF/DHF) has been an important public health challenge in Viet Nam and worldwide. This study was implemented in 2016-2017 using retrospective secondary data to explore associations between monthly DF/DHF cases and climate variables during 2008 to 2015. There were 48 175 DF/DHF cases reported, and the highest number of cases occurred in November. There were significant correlations between monthly DF/DHF cases with monthly mean of evaporation ( r = 0.236, P < .05), monthly relative humidity ( r = -0.358, P < .05), and monthly total hours of sunshine ( r = 0.389, P < .05). The results showed significant correlation in lag models but did not find direct correlations between monthly DF/DHF cases and monthly average rainfall and temperature. The study recommended that health staff in Hanoi should monitor DF/DHF cases at the beginning of epidemic period, starting from May, and apply timely prevention and intervention measures to avoid the spreading of the disease in the following months. A larger scale study for a longer period of time and adjusting for other potential influencing factors could better describe the correlations, modelling/projection, and developing an early warning system for the disease, which is important under the impacts of climate change and climate variability.

The associations between malaria, interventions, and the environment: a systematic review and meta-analysis

BACKGROUND

Malaria transmission is driven by multiple factors, including complex and multifaceted connections between malaria transmission, socioeconomic conditions, climate and interventions. Forecasting models should account for all significant drivers of malaria incidence although it is first necessary to understand the relationship between malaria burden and the various determinants of risk to inform the development of forecasting models. In this study, the associations between malaria risk, environmental factors, and interventions were evaluated through a systematic review.

METHODS

Five electronic databases (CAB Abstracts, EMBASE, Global Health, MEDLINE and ProQuest Dissertations & Theses) were searched for studies that included both the effects of the environment and interventions on malaria within the same statistical model. Studies were restricted to quantitative analyses and health outcomes of malaria mortality or morbidity, outbreaks, or transmission suitability. Meta-analyses were conducted on a subset of results using random-effects models.

RESULTS

Eleven studies of 2248 potentially relevant articles that met inclusion criteria were identified for the systematic review and two meta-analyses based upon five results each were performed. Normalized Difference Vegetation Index was not found to be statistically significant associated with malaria with a pooled OR of 1.10 (95% CI 0.07, 1.71). Bed net ownership was statistically associated with decreasing risk of malaria, when controlling for the effects of environment with a pooled OR of 0.75 (95% CI 0.60, 0.95). In general, environmental effects on malaria, while controlling for the effect of interventions, were variable and showed no particular pattern. Bed nets ownership, use and distribution, have a significant protective effect while controlling for environmental variables.

CONCLUSIONS

There are a limited number of studies which have simultaneously evaluated both environmental and interventional effects on malaria risk. Poor statistical reporting and a lack of common metrics were important challenges for this review, which must be addressed to ensure reproducibility and quality research. A comprehensive or inclusive approach to identifying malaria determinants using standardized indicators would allow for a better understanding of its epidemiology, which is crucial to improve future malaria risk estimations.

The links between agriculture, Anopheles mosquitoes, and malaria risk in children younger than 5 years in the Democratic Republic of the Congo: a population-based, cross-sectional, spatial study

BACKGROUND

The relationship between agriculture, Anopheles mosquitoes, and malaria in Africa is not fully understood, but it is important for malaria control as countries consider expanding agricultural projects to address population growth and food demand. Therefore, we aimed to assess the effect of agriculture on Anopheles biting behaviour and malaria risk in children in rural areas of the Democratic Republic of the Congo (DR Congo).

METHODS

We did a population-based, cross-sectional, spatial study of rural children (<5 years) in the DR Congo. We used information about the presence of malaria parasites in each child, as determined by PCR analysis of dried-blood spots from the 2013-14 DR Congo Demographic and Health Survey (DHS). We also used data from the DHS, a longitudinal entomological study, and available land cover and climate data to evaluate the relationships between agriculture, Anopheles biting behaviour, and malaria prevalence. Satellite imagery was used to measure the percentage of agricultural land cover around DHS villages and Anopheles sites. Anopheles biting behaviour was assessed by Human Landing Catch. We used probit regression to assess the relationship between agriculture and the probability of malaria infection, as well as the relationship between agriculture and the probability that a mosquito was caught biting indoors.

FINDINGS

Between Aug 13, 2013, and Feb 13, 2014, a total of 9790 dried-blood spots were obtained from the DHS, of which 4612 participants were included in this study. Falciparum malaria infection prevalence in rural children was 38·7% (95% uncertainty interval [UI] 37·3-40·0). Increasing exposure to agriculture was associated with increasing malaria risk with a high posterior probability (estimate 0·07, 95% UI -0·04 to 0·17; posterior probability [estimate >0]=0·89), with the probability of malaria infection increased between 0·2% (95% UI -0·1 to 3·4) and 2·6% (-1·5 to 6·6) given a 15% increase in agricultural cover, depending on other risk factors. The models predicted that large increases in agricultural cover (from 0% to 75%) increase the probability of infection by as much as 13·1% (95% UI -7·3 to 28·9). Increased risk might be due to Anopheles gambiae sensu lato, whose probability of biting indoors increased between 11·3% (95% UI -15·3 to 25·6) and 19·7% (-12·1 to 35·9) with a 15% increase in agriculture.

INTERPRETATION

Malaria control programmes must consider the possibility of increased risk due to expanding agriculture. Governments considering initiating large-scale agricultural projects should therefore also consider accompanying additional malaria control measures.

FUNDING

National Institutes of Health, National Science Foundation, Bill & Melinda Gates Foundation, President's Malaria Initiative, and Royster Society of Fellows at the University of North Carolina at Chapel Hill.

Present and Future of Dengue Fever in Nepal: Mapping Climatic Suitability by Ecological Niche Model

Both the number of cases of dengue fever and the areas of outbreaks within Nepal have increased significantly in recent years. Further expansion and range shift is expected in the future due to global climate change and other associated factors. However, due to limited spatially-explicit research in Nepal, there is poor understanding about the present spatial distribution patterns of dengue risk areas and the potential range shift due to future climate change. In this context, it is crucial to assess and map dengue fever risk areas in Nepal. Here, we used reported dengue cases and a set of bioclimatic variables on the MaxEnt ecological niche modeling approach to model the climatic niche and map present and future (2050s and 2070s) climatically suitable areas under different representative concentration pathways (RCP2.6, RCP6.0 and RCP8.5). Simulation-based estimates suggest that climatically suitable areas for dengue fever are presently distributed throughout the lowland Tarai from east to west and in river valleys at lower elevations. Under the different climate change scenarios, these areas will be slightly shifted towards higher elevation with varied magnitude and spatial patterns. Population exposed to climatically suitable areas of dengue fever in Nepal is anticipated to further increase in both 2050s and 2070s on all the assumed emission scenarios. These findings could be instrumental to plan and execute the strategic interventions for controlling dengue fever in Nepal.

Climate Variability and Dengue Hemorrhagic Fever in Ba Tri District, Ben Tre Province, Vietnam during 2004-2014

Background

Currently, dengue fever/dengue hemorrhagic fever (DF/DHF) is an important public health challenge in many areas, including the Ba Tri District, Ben Tre Province, Vietnam.

Methods and Aim

This study was conducted in 2015 using a retrospective secondary data analysis on monthly data of DF/DHF cases and climate conditions from 2004-2014 in Ba Tri District, which aimed to explore the relationship between DF/DHF and climate variables.

Results

During the period of 2004-2014, there were 5728 reported DF/DHF cases and five deaths. The disease occurred year round, with peaked from May to October and the highest number of cases occurred in June and July. There were strong correlations between monthly DF/DHF cases within that period with average rainfall (r = 0.70), humidity (r = 0.59), mosquito density (r = 0.82), and Breteau index (r = 0.81). A moderate association was observed between the monthly average number of DF/DHF cases and the average temperature (r = 0.37). The monthly DF/DHF cases were also moderately correlated with the Aedes mosquito density.

Conclusions and Recommendations

Local health authorities need to monitor DF/DHF cases at the beginning of epidemic period, starting from April and to apply timely disease prevention measures to avoid the spreading of the disease in the following months. More vector control efforts should be implemented in March and April, just before the rainy season, which can help to reduce the vector density and the epidemic risk. A larger scale study using national data and for a longer period of time should be undertaken to thoroughly describe the correlation between climate variability and DF/DHF cases as well as for modeling and building projection model for the disease in the coming years. This can play an important role for active prevention of DF/DHF in Vietnam under the impacts of climate change and weather variability.

Alarm Variables for Dengue Outbreaks: A Multi-Centre Study in Asia and Latin America

BACKGROUND

Worldwide, dengue is an unrelenting economic and health burden. Dengue outbreaks have become increasingly common, which place great strain on health infrastructure and services. Early warning models could allow health systems and vector control programmes to respond more cost-effectively and efficiently.

METHODOLOGY/PRINCIPAL FINDINGS

The Shewhart method and Endemic Channel were used to identify alarm variables that may predict dengue outbreaks. Five country datasets were compiled by epidemiological week over the years 2007-2013. These data were split between the years 2007-2011 (historic period) and 2012-2013 (evaluation period). Associations between alarm/ outbreak variables were analysed using logistic regression during the historic period while alarm and outbreak signals were captured during the evaluation period. These signals were combined to form alarm/ outbreak periods, where 2 signals were equal to 1 period. Alarm periods were quantified and used to predict subsequent outbreak periods. Across Mexico and Dominican Republic, an increase in probable cases predicted outbreaks of hospitalised cases with sensitivities and positive predictive values (PPV) of 93%/ 83% and 97%/ 86% respectively, at a lag of 1-12 weeks. An increase in mean temperature ably predicted outbreaks of hospitalised cases in Mexico and Brazil, with sensitivities and PPVs of 79%/ 73% and 81%/ 46% respectively, also at a lag of 1-12 weeks. Mean age was predictive of hospitalised cases at sensitivities and PPVs of 72%/ 74% and 96%/ 45% in Mexico and Malaysia respectively, at a lag of 4-16 weeks.

CONCLUSIONS/SIGNIFICANCE

An increase in probable cases was predictive of outbreaks, while meteorological variables, particularly mean temperature, demonstrated predictive potential in some countries, but not all. While it is difficult to define uniform variables applicable in every country context, the use of probable cases and meteorological variables in tailored early warning systems could be used to highlight the occurrence of dengue outbreaks or indicate increased risk of dengue transmission.

Global Climate Change and Children's Health

Rising global temperature is causing major physical, chemical, and ecological changes across the planet. There is wide consensus among scientific organizations and climatologists that these broad effects, known as climate change, are the result of contemporary human activity. Climate change poses threats to human health, safety, and security. Children are uniquely vulnerable to these threats. The effects of climate change on child health include physical and psychological sequelae of weather disasters, increased heat stress, decreased air quality, altered disease patterns of some climate-sensitive infections, and food, water, and nutrient insecurity in vulnerable regions. Prompt implementation of mitigation and adaptation strategies will protect children against worsening of the problem and its associated health effects. This technical report reviews the nature of climate change and its associated child health effects and supports the recommendations in the accompanying policy statement on climate change and children's health.

Infectious Diseases, Urbanization and Climate Change: Challenges in Future China

China is one of the largest countries in the world with nearly 20% of the world's population. There have been significant improvements in economy, education and technology over the last three decades. Due to substantial investments from all levels of government, the public health system in China has been improved since the 2003 severe acute respiratory syndrome (SARS) outbreak. However, infectious diseases still remain a major population health issue and this may be exacerbated by rapid urbanization and unprecedented impacts of climate change. This commentary aims to explore China's current capacity to manage infectious diseases which impair population health. It discusses the existing disease surveillance system and underscores the critical importance of strengthening the system. It also explores how the growing migrant population, dramatic changes in the natural landscape following rapid urbanization, and changing climatic conditions can contribute to the emergence and re-emergence of infectious disease. Continuing research on infectious diseases, urbanization and climate change may inform the country's capacity to deal with emerging and re-emerging infectious diseases in the future.

Correlations Between the Incidence of National Notifiable Infectious Diseases and Public Open Data, Including Meteorological Factors and Medical Facility Resources

OBJECTIVES

This study was performed to investigate the relationship between the incidence of national notifiable infectious diseases (NNIDs) and meteorological factors, air pollution levels, and hospital resources in Korea.

METHODS

We collected and stored 660,000 pieces of publicly available data associated with infectious diseases from public data portals and the Diseases Web Statistics System of Korea. We analyzed correlations between the monthly incidence of these diseases and monthly average temperatures and monthly average relative humidity, as well as vaccination rates, number of hospitals, and number of hospital beds by district in Seoul.

RESULTS

Of the 34 NNIDs, malaria showed the most significant correlation with temperature (r=0.949, p<0.01) and concentration of nitrogen dioxide (r=-0.884, p<0.01). We also found a strong correlation between the incidence of NNIDs and the number of hospital beds in 25 districts in Seoul (r=0.606, p<0.01). In particular, Geumcheon-gu was found to have the lowest incidence rate of NNIDs and the highest number of hospital beds per patient.

CONCLUSIONS

In this study, we conducted a correlational analysis of public data from Korean government portals that can be used as parameters to forecast the spread of outbreaks.

Multisensor earth observations to characterize wetlands and malaria epidemiology in Ethiopia

Malaria is a major global public health problem, particularly in Sub-Saharan Africa. The spatial heterogeneity of malaria can be affected by factors such as hydrological processes, physiography, and land cover patterns. Tropical wetlands, for example, are important hydrological features that can serve as mosquito breeding habitats. Mapping and monitoring of wetlands using satellite remote sensing can thus help to target interventions aimed at reducing malaria transmission. The objective of this study was to map wetlands and other major land cover types in the Amhara region of Ethiopia and to analyze district-level associations of malaria and wetlands across the region. We evaluated three random forests classification models using remotely sensed topographic and spectral data based on Shuttle Radar Topographic Mission (SRTM) and Landsat TM/ETM+ imagery, respectively. The model that integrated data from both sensors yielded more accurate land cover classification than single-sensor models. The resulting map of wetlands and other major land cover classes had an overall accuracy of 93.5%. Topographic indices and subpixel level fractional cover indices contributed most strongly to the land cover classification. Further, we found strong spatial associations of percent area of wetlands with malaria cases at the district level across the dry, wet, and fall seasons. Overall, our study provided the most extensive map of wetlands for the Amhara region and documented spatiotemporal associations of wetlands and malaria risk at a broad regional level. These findings can assist public health personnel in developing strategies to effectively control and eliminate malaria in the region.

KEY POINTS

Remote sensing produced an accurate wetland map for the Ethiopian highlandsWetlands were associated with spatial variability in malaria riskMapping and monitoring wetlands can improve malaria spatial decision support.

Old health risks in new places? An ecological niche model for I. ricinus tick distribution in Europe under a changing climate

Climate change will likely have impacts on disease vector distribution. Posing a significant health threat in the 21st century, risk of tick-borne diseases may increase with higher annual mean temperatures and changes in precipitation. We modeled the current and future potential distribution of the Ixodes ricinus tick species in Europe. The Genetic Algorithm for Rule-set Prediction (GARP) was utilized to predict potential distributions of I. ricinus based on current (1990-2010 averages) and future (2040-2060 averages) environmental variables. A ten model best subset was created out of a possible 200 models based on omission and commission criteria. Our results show that under the A2 climate change scenario the potential habitat range for the I. ricinus tick in Europe will expand into higher elevations and latitudes (e.g., Scandinavia, the Baltics, and Belarus), while contracting in other areas (e.g., Alps, Pyrenees, interior Italy, and northwestern Poland). Overall, a potential habitat expansion of 3.8% in all of Europe is possible. Our results may be used to inform climate change adaptation efforts in Europe.

Monitoring population and environmental parameters of invasive mosquito species in Europe

To enable a better understanding of the overwhelming alterations in the invasive mosquito species (IMS), methodical insight into the population and environmental factors that govern the IMS and pathogen adaptations are essential. There are numerous ways of estimating mosquito populations, and usually these describe developmental and life-history parameters. The key population parameters that should be considered during the surveillance of invasive mosquito species are: (1) population size and dynamics during the season, (2) longevity, (3) biting behaviour, and (4) dispersal capacity. Knowledge of these parameters coupled with vector competence may help to determine the vectorial capacity of IMS and basic disease reproduction number (R0) to support mosquito borne disease (MBD) risk assessment. Similarly, environmental factors include availability and type of larval breeding containers, climate change, environmental change, human population density, increased human travel and goods transport, changes in living, agricultural and farming habits (e.g. land use), and reduction of resources in the life cycle of mosquitoes by interventions (e.g. source reduction of aquatic habitats). Human population distributions, urbanisation, and human population movement are the key behavioural factors in most IMS-transmitted diseases. Anthropogenic issues are related to the global spread of MBD such as the introduction, reintroduction, circulation of IMS and increased exposure to humans from infected mosquito bites. This review addresses the population and environmental factors underlying the growing changes in IMS populations in Europe and confers the parameters selected by criteria of their applicability. In addition, overview of the commonly used and newly developed tools for their monitoring is provided.

Temporal pattern of questing tick Ixodes ricinus density at differing elevations in the coastal region of western Norway

Background

Climate change can affect the activity and distribution of species, including pathogens and parasites. The densities and distribution range of the sheep tick (Ixodes ricinus) and it’s transmitted pathogens appears to be increasing. Thus, a better understanding of questing tick densities in relation to climate and weather conditions is urgently needed. The aim of this study was to test predictions regarding the temporal pattern of questing tick densities at two different elevations in Norway. We predict that questing tick densities will decrease with increasing elevations and increase with increasing temperatures, but predict that humidity levels will rarely affect ticks in this northern, coastal climate with high humidity.

Methods

We described the temporal pattern of questing tick densities at ~100 and ~400 m a.s.l. along twelve transects in the coastal region of Norway. We used the cloth lure method at 14-day intervals during the snow-free season to count ticks in two consecutive years in 20 m² plots. We linked the temporal pattern of questing tick densities to local measurements of the prevailing weather.

Results

The questing tick densities were much higher and the season was longer at ~100 compared to at ~400 m a.s.l. There was a prominent spring peak in both years and a smaller autumn peak in one year at ~100 m a.s.l.; but no marked peak at ~400 m a.s.l. Tick densities correlated positively with temperature, from low densities <5°C, then increasing and levelling off >15-17°C. We found no evidence for reduced questing densities during the driest conditions measured.

Conclusions

Tick questing densities differed even locally linked to elevation (on the same hillside, a few kilometers apart). The tick densities were strongly hampered by low temperatures that limited the duration of the questing seasons, whereas the humidity appeared not to be a limiting factor under the humid conditions at our study site. We expect rising global temperatures to increase tick densities and lead to a transition from a short questing season with low densities in the current cold and sub-optimal tick habitats, to longer questing seasons with overall higher densities and a marked spring peak.

Habitat hydrology and geomorphology control the distribution of malaria vector larvae in rural Africa

Background

Larval source management is a promising component of integrated malaria control and elimination. This requires development of a framework to target productive locations through process-based understanding of habitat hydrology and geomorphology.

Methods

We conducted the first catchment scale study of fine resolution spatial and temporal variation in Anopheles habitat and productivity in relation to rainfall, hydrology and geomorphology for a high malaria transmission area of Tanzania.

Results

Monthly aggregates of rainfall, river stage and water table were not significantly related to the abundance of vector larvae. However, these metrics showed strong explanatory power to predict mosquito larval abundances after stratification by water body type, with a clear seasonal trend for each, defined on the basis of its geomorphological setting and origin.

Conclusion

Hydrological and geomorphological processes governing the availability and productivity of Anopheles breeding habitat need to be understood at the local scale for which larval source management is implemented in order to effectively target larval source interventions. Mapping and monitoring these processes is a well-established practice providing a tractable way forward for developing important malaria management tools.

Temporal modeling of Crimean-Congo hemorrhagic fever in eastern Iran

OBJECTIVES

This study was conducted to determine the predicting factors of Crimean Congo hemorrhagic fever (CCHF) in Zabol and Zahedan, from where more than 60% of all national cases are reported, in order to improve CCHF disease surveillance and to target control efforts.

METHODS

Data were collected from the National Reference Laboratory on Arboviruses and Viral Hemorrhagic Fevers, the national meteorology organization, the veterinary organization, and the national statistics center of Iran. A Poisson regression analysis was applied for the temporal modeling of human samples between 2000 and 2006. The modeling fitness was checked with data from 2007.

RESULTS

This modeling revealed that the disease occurrence followed a seasonal pattern. The maximum temperature and relative humidity in previous months was found to positively affect the occurrence of the disease. Variables such as the level of livestock imports and the number of slaughtered animals were also found to be influential in the occurrence of the disease. The pseudo R(2) was 0.51 in the final model.

CONCLUSIONS

The model predicted the number of cases 1 month in advance with more or less acceptable accuracy. Therefore, it appears that the model might be useful as part of an early warning system.

Climate change and animal diseases: making the case for adaptation

The exponential expansion of the human population has led to overexploitation of resources and overproduction of items that have caused a series of potentially devastating effects, including ocean acidification, ozone depletion, biodiversity loss, the spread of invasive flora and fauna and climatic changes – along with the emergence of new diseases in animals and humans. Climate change occurs as a result of imbalances between incoming and outgoing radiation in the atmosphere. This process generates heat. As concentrations of atmospheric gases reach record levels, global temperatures are expected to increase significantly. The hydrologic cycle will be altered, since warmer air can retain more moisture than cooler air. This means that some geographic areas will have more rainfall, whereas others have more drought and severe weather. The potential consequences of significant and permanent climatic changes are altered patterns of diseases in animal and human populations, including the emergence of new disease syndromes and changes in the prevalence of existing diseases. A wider geographic distribution of known vectors and the recruitment of new strains to the vector pool could result in infections spreading to more and potentially new species of hosts. If these predictions turn out to be accurate, there will be a need for policymakers to consider alternatives, such as adaptation. This review explores the linkages between climate change and animal diseases, and examines interrelated issues that arise from altered biological dynamics. Its aim is to consider various risks and vulnerabilities and to make the case for policies favoring adaptation.

Weather-driven variation in dengue activity in Australia examined using a process-based modeling approach

The impact of weather variation on dengue transmission in Cairns, Australia, was determined by applying a process-based dengue simulation model (DENSiM) that incorporated local meteorologic, entomologic, and demographic data. Analysis showed that inter-annual weather variation is one of the significant determinants of dengue outbreak receptivity. Cross-correlation analyses showed that DENSiM simulated epidemics of similar relative magnitude and timing to those historically recorded in reported dengue cases in Cairns during 1991-2009, (r = 0.372, P < 0.01). The DENSiM model can now be used to study the potential impacts of future climate change on dengue transmission. Understanding the impact of climate variation on the geographic range, seasonality, and magnitude of dengue transmission will enhance development of adaptation strategies to minimize future disease burden in Australia.

Dengue vector surveillance programs: a review of methodological diversity in some endemic and epidemic countries

Vector surveillance is a cornerstone of dengue management yet there is a diversity of surveillance programs evident internationally. Such diversity is described in this review to enable a broader assessment of dengue vector surveillance methods. This review describes the diversity of surveillance programs for dengue vectors in several endemic and epidemic countries. Furthermore, strengths and weaknesses of vector surveillance methods, including larval surveys, BG-Sentinel trap, and autocidal and sticky ovitraps, are also discussed. The ability to compare and contrast these programs could contribute to the finding of better methods both locally and nationally and facilitate interregional technology transfer. Health authorities in both endemic and epidemic countries alike could benefit from adopting technologies and practices from other regions.

Factors associated with acute mountain sickness in young Chinese men on entering highland areas

AIM

The aim of this study was to explore the prediction factors for incidence of acute mountain sickness (AMS) in young males newly entering highland areas.

METHODS

A retrospective study of 4367 records of male highland soldiers from 2000 to 2005 was done. The factors were tested by logistic regression.

RESULTS

After selection by univariate model, ethnicity, altitude, season, deployment type, and prophylaxis were inserted into a multivariate model. The adjusted odds ratio (AOR) was 0.078 for Tibetan compared with Han. AORs for altitudes 3600 to 3700, 4000 to 4300, and 4600 to 4700 m versus 2900 to 3100 m were 4.490, 4.532, and 4.964, respectively. AOR for cold season versus warm season was 1.332. AORs for emergency land deployment and air deployment versus normal land deployment were 2.261 and 1.614, respectively. The AOR was 0.741 for prophylaxis versus none. The area under receiver operating characteristic curve was 0.731 (optimal cutoff = 0.370).

CONCLUSIONS

Adjusting for altitude, risk factors that contributed to AMS were being non-Tibetan, cold season, greater speed of transport, emergency conditions, and without prophylaxis. The model established is acceptable for assisting AMS prediction.

Changing landscape of malaria in China: progress and feasibility of malaria elimination

Large-scale malaria control activities in China have been conducted with significant success, since the launch of the nationwide malaria control program. This study investigated the malaria distribution in China, particularly in provinces with high risks. Spatial and temporal data were assembled for all endemic or historically endemic areas and combined to identify common patterns and to investigate the actual changes in the burden of malaria in the country. Data were analyzed and the progress in malaria elimination feasibility was discussed. The results indicated that the current distribution of malaria and vectors associated could provide evidence on the assessment of the feasibility of the malaria elimination in China.

Abiotic Determinants to the Spatial Dynamics of Dengue Fever in Guangzhou

Dengue fever (DF) is a mosquito-borne disease that significantly endangers the well-being of people in most tropical Asia-Pacific areas. The transmission of DF is inherently a spatial process, requiring susceptible humans encountering infectious mosquito. The relationships between humans, mosquito and environment underpin the dynamics and patterns of the epidemic. In this article, the objective is to find out the key abiotic factors in the spatial dynamics of DF. An interdisciplinary study has been carried out by taking advantage of statistics, geographical information science, and remote sensing technologies. The case study is the DF outbreak in the Chinese city of Guangzhou throughout the year of 2002—the most serious DF outbreak in the recent decade. This study shows that the presence and abundance of DF cases can be associated with ( a) socioeconomic factors relating to urbanization and ( b) meteorological factors favoring mosquito survival.

Population density, water supply, and the risk of dengue fever in Vietnam: cohort study and spatial analysis

BACKGROUND

Aedes aegypti, the major vector of dengue viruses, often breeds in water storage containers used by households without tap water supply, and occurs in high numbers even in dense urban areas. We analysed the interaction between human population density and lack of tap water as a cause of dengue fever outbreaks with the aim of identifying geographic areas at highest risk.

METHODS AND FINDINGS

We conducted an individual-level cohort study in a population of 75,000 geo-referenced households in Vietnam over the course of two epidemics, on the basis of dengue hospital admissions (n = 3,013). We applied space-time scan statistics and mathematical models to confirm the findings. We identified a surprisingly narrow range of critical human population densities between around 3,000 to 7,000 people/km² prone to dengue outbreaks. In the study area, this population density was typical of villages and some peri-urban areas. Scan statistics showed that areas with a high population density or adequate water supply did not experience severe outbreaks. The risk of dengue was higher in rural than in urban areas, largely explained by lack of piped water supply, and in human population densities more often falling within the critical range. Mathematical modeling suggests that simple assumptions regarding area-level vector/host ratios may explain the occurrence of outbreaks.

CONCLUSIONS

Rural areas may contribute at least as much to the dissemination of dengue fever as cities. Improving water supply and vector control in areas with a human population density critical for dengue transmission could increase the efficiency of control efforts. Please see later in the article for the Editors' Summary.

Climate change and infectious diseases in Australia: future prospects, adaptation options, and research priorities

Climate change will have significant and diverse impacts on human health. These impacts will include changes in infectious disease incidence. In this article, the authors review the current situation and potential future climate change impacts for respiratory, diarrheal, and vector-borne diseases in Australia. Based on this review, the authors suggest adaptive strategies within the health sector and also recommend future research priorities.

Modeling the relationship between precipitation and malaria incidence in children from a holoendemic area in Ghana

Climatic factors influence the incidence of vector-borne diseases such as malaria. They modify the abundance of mosquito populations, the length of the extrinsic parasite cycle in the mosquito, the malarial dynamics, and the emergence of epidemics in areas of low endemicity. The objective of this study was to investigate temporal associations between weekly malaria incidence in 1,993 children < 15 years of age and weekly rainfall. A time series analysis was conducted by using cross-correlation function and autoregressive modeling. The regression model showed that the level of rainfall predicted the malaria incidence after a time lag of 9 weeks (mean = 60 days) and after a time lag between one and two weeks. The analyses provide evidence that high-resolution precipitation data can directly predict malaria incidence in a highly endemic area. Such models might enable the development of early warning systems and support intervention measures.

Potential malaria outbreak in Germany due to climate warming: risk modelling based on temperature measurements and regional climate models

PURPOSE

Climate warming can change the geographic distribution and intensity of the transmission of vector-borne diseases such as malaria. The transmitted parasites usually benefit from increased temperatures as both their reproduction and development are accelerated. Lower Saxony (northwestern Germany) has been a malaria region until the 1950s, and the vector species are still present throughout Germany. This gave reason to investigate whether a new autochthonous transmission could take place if the malaria pathogen was introduced again in Germany.

MATERIALS AND METHODS

The spatial distribution of potential temperature-driven malaria transmissions was investigated using the basic reproduction rate (R (0)) to model and geostatistically map areas at risk of an outbreak of tertian malaria based on measured (1961-1990, 1991-2007) and predicted (1991-2020, 2021-2050, 2051-2080) monthly mean air temperature data.

RESULTS

From the computations, maps were derived showing that during the period 1961-1990, the seasonal transmission gate ranges from 0 to 4 months and then expands up to 5 months in the period 1991-2007. For the projection of future trends, the regional climate models REMO and WettReg were used each with two different scenarios (A1B and B1). Both modelling approaches resulted in prolonged seasonal transmission gates in the future, enabling malaria transmissions up to 6 months in the climate reference period 2051-2080 (REMO, scenario A1B).

DISCUSSION

The presented risk prognosis is based on the R (0) formula for the estimation of the reproduction of the malaria pathogen Plasmodium vivax. The presented model focuses on mean air temperatures; thus, other driving factors like the distribution of water bodies (breeding habitats) or population density are not integrated. Nevertheless, the modelling presented in this study can help identify areas at risk and initiate prevention. The described findings may also help in the investigation and assessment of related diseases caused by temperature-dependent vectors and pathogens, including those being dangerous for livestock as well, e.g. insect-borne bluetongue disease transmitted by culicoids.

[Correlations between climate change-related infectious diseases and meteorological factors in Korea]

OBJECTIVES

Infectious diseases are known to be affected by climate change. We investigated if the infectious diseases were related to meteorological factors in Korea.

METHODS

Scrub typhus, hemorrhagic fever with renal syndrome (HFRS), leptospirosis, malaria and Vibrio vulnificus sepsis among the National Notifiable Infectious Diseases were selected as the climate change-related infectious diseases. Temperature, relative humidity and precipitation were used as meteorological factors. The study period was from 2001 through 2008. We examined the seasonality of the diseases and those correlations with meteorological factors. We also analyzed the correlations between the incidences of the diseases during the outbreak periods and monthly meteorological factors in the hyper-endemic regions.

RESULTS

All of the investigated diseases showed strong seasonality; malaria and V. vulnificus sepsis were prevalent in summer and scrub typhus, HFRS and leptospirosis were prevalent in the autumn. There were significant correlations between the monthly numbers of cases and all the meteorological factors for malaria and V. vulnificus sepsis, but there were no correlation for the other diseases. However, the incidence of scrub typhus in hyper-endemic region during the outbreak period was positively correlated with temperature and humidity during the summer. The incidences of HFRS and leptospirosis had positive correlations with precipitation in November and temperature and humidity in February, respectively. V. vulnificus sepsis showed positive correlations with precipitation in April/May/July.

CONCLUSIONS

In Korea, the incidences of the infectious diseases were correlated with meteorological factors, and this implies that the incidences could be influenced by climate change.

Beyond temperature and precipitation: ecological risk factors that modify malaria transmission

Being able to identify the ecological factors that impact risk for malaria would confer important predictive capacity to target malaria control interventions in a community. Temperature and water available for breeding habitats have been shown to be important primary ecological factors that impact the distribution of the malaria vectors and the rate at which the mosquito and parasite develop. However, to this point, studies focusing on the local level have been met with many inconsistent results when assessing malaria risk using both temperature and precipitation. This paper reviewed existing literature to determine if other ecological factors beyond temperature and water are present that may be modifying any associations present between ecological factors and malaria risk. It was found that the ability for water to pool and persist, water quality, elevation, deforestation, and agriculture have all been associated with malaria and may be modifying risk. Using the primary and modifying ecological variables, identifying the interactions between these factors and specific thresholds for increased malaria risk is critical: filling this knowledge gap would enable communities to develop tailored malaria control interventions targeted to their specific circumstances.

Climate change, vector-borne disease and interdisciplinary research: social science perspectives on an environment and health controversy

Over the last two decades, the science of climate change's theoretical impacts on vector-borne disease has generated controversy related to its methodological validity and relevance to disease control policy. Critical social science analysis, drawing on science and technology studies and the sociology of social movements, demonstrates consistency between this controversy and the theory that climate change is serving as a collective action frame for some health researchers. Within this frame, vector-borne disease data are interpreted as a symptom of climate change, with the need for further interdisiplinary research put forth as the logical and necessary next step. Reaction to this tendency on the part of a handful of vector-borne disease specialists exhibits characteristics of academic boundary work aimed at preserving the integrity of existing disciplinary boundaries. Possible reasons for this conflict include the leadership role for health professionals and disciplines in the envisioned interdiscipline, and disagreements over the appropriate scale of interventions to control vector-borne diseases. Analysis of the competing frames in this controversy also allows identification of excluded voices and themes, such as international political economic explanations for the health problems in question. A logical conclusion of this analysis, therefore, is the need for critical reflection on environment and health research and policy to achieve integration with considerations of global health equity.

Mitigation/adaptation and health: health policymaking in the global response to climate change and implications for other upstream determinants

The time is ripe for innovation in global health governance if we are to achieve global health and development objectives in the face of formidable challenges. Integration of global health concerns into the law and governance of other, related disciplines should be given high priority. This article explores opportunities for health policymaking in the global response to climate change. Climate change and environmental degradation will affect weather disasters, food and water security, infectious disease patterns, and air pollution. Although scientific research has pointed to the interdependence of the global environment and human health, policymakers have been slow to integrate their approaches to environmental and health concerns. A robust response to climate change will require improved integration on two fronts: health concerns must be given higher priority in the response to climate change and threats associated with climate change and environmental degradation must be more adequately addressed by global health law and governance. The mitigation/adaptation response paradigm developing within and beyond the United Nations Framework Convention on Climate Change provides a useful framework for thinking about global health law and governance with respect to climate change, environmental degradation, and possibly other upstream determinants of health as well.

Public Health Responses to Climate Change Health Impacts in Indonesia

Although climate change is a global concern, there are particular considerations for Indonesia as an archipelagic nation. These include the vulnerability of people living in small islands and coastal areas to rising sea levels; the expansion of the important mosquito-borne diseases, particularly malaria and dengue, into areas that lack of immunity; and the increase in water-borne diseases and malnutrition. This article proposes a set of public health responses to climate change health impacts in Indonesia. Some important principles and practices in public health are highlighted, to develop effective public health approaches to climate change in Indonesia.