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- Ahmed Hassan Ahmed, Osama, 1972-
(författare)
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Rift Valley fever : challenges and new insights for prevention and control using the “One Health” approach
- 2016
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Rift Valley fever (RVF) is an emerging viral zoonosis that causes frequent outbreaks in east Africa and on the Arabian Peninsula. The likelihood of RVF global expansion due to climate change and human anthropogenic factors is an important issue. The causative agent, RVF virus, is an arbovirus that is transmitted by several mosquito species and is able to infect a wide range of livestock as well as people. The infection leads to mass abortions and death in livestock and a potentially deadly hemorrhagic fever in humans. RVF has severe socio-economic consequences such as animal trade bans between countries, disruption of food security, and economic disaster for farmers and pastoralists as well as for countries. Human behavior such as direct contact with infected animals or their fluids and exposure to mosquito bites increases the risk for contracting the disease.To better understand the challenges associated with RVF outbreaks and to explore prevention and control strategies, we used the One Health approach. The local community had to be involved to understand the interaction between the environment, animals, and humans. We focused on Sudan, Saudi Arabia, and Kenya. First, we systematically reviewed the literature and then we performed cross sectional community-based studies using a special One Health questionnaire. Climatic and remote sensing data were used in combination with statistics to develop a sub-region predictive model for RVF.For both Saudi Arabia and Sudan, the ecology and environment of the affected areas were similar. These areas included irrigation canals and excessive rains that provide an attractive habitat for mosquito vectors to multiply. The surveillance systems were unable to detect the virus in livestock before it spread to humans. Ideally, livestock should serve as sentinels to prevent loss of human lives, but the situation here was reversed. Differences between countries regarding further spread of RVF was mainly determined by better economic and infrastructure resources.In Sudan, there was a lack of knowledge and appropriate practices at the studied community regarding RVF disease symptoms and risk factors for both animals and humans. The community was hesitant in notifying the authorities about RVF suspicion in livestock due to the lack of a compensation system. The perceived role of the community in controlling RVF was fragmented, increasing the probability of RVF transmission and disease.In Kenya, our study found that better knowledge about RVF does not always translate to more appropriate practices that avoid exposure to the disease. However, the combination of good knowledge, attitudes, and practices may explain why certain communities were less affected. Strategies to combat RVF should consider socio-cultural and behavioral differences among communities. We also noticed that RVF outbreaks in Kenya occurred in regions with high livestock density exposed to heavy rains and wet soil fluxes, which could be measured by evapotranspiration and vegetation seasonality variables. We developed a RVF risk map on a sub-regional scale. Future outbreaks could be better managed if such relevant RVF variables are integrated into early warning systems.To confront RVF outbreaks, a policy is needed that better incorporates ecological factors and human interactions with livestock and environment that help the RVF pathogen spread. Early detection and notification of RVF is essential because a delay will threaten the core of International Health Regulations (IHR), which emphasizes the share of information during a transboundary disease outbreak to avoid unnecessary geographical expansion.
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- Egondi, Thaddaeus Wandera, 1978-
(författare)
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Making visible the invisible : Health risks from environmental exposures among socially deprived populations of Nairobi, Kenya
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Background: Most countries of sub-Saharan Africa (SSA) are experiencing a high rate of urbanization accompanied with unplanned development resulting into sprawl of slums. The weather patterns and air pollution sources in most urban areas are changing with significant effects on health. Studies have established a link between environmental exposures, such as weather variation and air pollution, and adverse health outcomes. However, little is known about this relationship in urban populations of SSA where more than half the population reside in slums, or slum like conditions. A major reason for this is the lack of systematic collection of data on exposure and health outcomes. High quality prospective data collection and census registers still remain a great challenge. However, within small and spatially defined areas, dynamic cohorts have been established with continuous monitoring of health outcomes. Collection of environmental exposure data can complement cohort studies to investigate health effects in relation to environmental exposures. The objective of this research was to study the health effects of selected environmental exposure among the urban poor population in Nairobi, Kenya.Methods: We used the platform of the Nairobi Urban Health and Demographic Surveillance System (NUHDSS), including two nested research studies, to provide data on mortality and morbidity. The NUHDSS was established in two areas of Nairobi, Korogocho and Viwandani, in 2003 and provides a unique opportunity for access to longitudinal population data. In addition, we conducted real-time measurements of particulate matter (PM2.5) in the areas from February to October in 2013. We obtained meteorological measurements from the Moi Air Base and Nairobi airport weather stations for the study period. We also conducted a cross-sectional survey to establish the communities’ perceptions about air pollution and its related health risks. Time series regression models with a distributed lag approach were used to model the relationship between weather and mortality. A semi-ecological study with group level exposure assignment to individuals was used to assess the relationship between child health (morbidity and mortality) and the extent of PM2.5 exposure.Results: There was a significant association between daily mean temperature and all-cause mortality with minimum mortality temperature (MMT) in the range of 18 to 20 °C. Both mortality risk and years of life lost analysis showed risk increases in relation to cold temperatures, with pronounced effect among children under-five. Overall, mortality risks were found to be high during cold periods of the year, rising with lower temperature from MMT to about 40% in the 0–4 age group, and by about v 20% among all ages. The results from air pollution assessment showed high levels of PM2.5 concentration exceeding World Health Organization (WHO) guideline limits in the two study areas. The air pollution concentration showed similar seasonal and diurnal variation in the two slums. The majority of community residents reported to be exposed to air pollution at work, with 66% reporting to be exposed to different sources of air pollution. Despite the observed high level of exposure, residents had poor perception of air pollution levels and associated health risks. Children in the high-pollution areas (PM2.5≥ 25 μg⁄m3) were at significantly higher risk for morbidity (OR = 1.30, 95% CI: 1.13-1.48) and cough as the only form of morbidity (OR = 1.33, 95% CI: 1.15-1.53) compared to those in low-pollution areas. In addition, exposure to high levels of pollution was associated with high child mortality from all-causes (IRR=1.15, 95% CI: 1.03-1.28), and indicated a positive association to respiratory related mortality (IRR=1.10, 95% CI: 0.91-1.33).Conclusion: The study findings extend our knowledge on health impacts related to environmental exposure by providing novel evidence on the risks in disadvantaged urban populations in Africa. More specifically, the study illustrates the invisible health burden that the urban poor population are facing in relation to weather and air pollution exposures. The effect of cold on population is preventable. This is manifested by the effective adaptation to cold conditions in high-latitude Nordic countries by housing standards and clothing, as well as a well-functioning health system. Further, awareness and knowledge of consequences, and reductions in exposure to air pollution, are necessary to improve public health in the slum areas. In conclusion, adverse health impacts caused by environmental stressors are critical to assess further in disadvantaged populations, and should be followed by development of mitigation measures leading to improved health and well being in SSA.
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- Hii, Yien Ling, 1962-
(författare)
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Climate and dengue fever : early warning based on temperature and rainfall
- 2013
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Background: Dengue is a viral infectious disease that is transmitted by mosquitoes. The disease causes a significant health burden in tropical countries, and has been a public health burden in Singapore for several decades. Severe complications such as hemorrhage can develop and lead to fatal outcomes. Before tetravalent vaccine and drugs are available, vector control is the key component to control dengue transmission. Vector control activities need to be guided by surveillance of outbreak and implement timely action to suppress dengue transmission and limit the risk of further spread. This study aims to explore the feasibility of developing a dengue early warning system using temperature and rainfall as main predictors. The objectives were to 1) analyze the relationship between dengue cases and weather predictors, 2) identify the optimal lead time required for a dengue early warning, 3) develop forecasting models, and 4) translate forecasts to dengue risk indices.Methods: Poisson multivariate regression models were established to analyze relative risks of dengue corresponding to each unit change of weekly mean temperature and cumulative rainfall at lag of 1-20 weeks. Duration of vector control for localized outbreaks was analyzed to identify the time required by local authority to respond to an early warning. Then, dengue forecasting models were developed using Poisson multivariate regression. Autoregression, trend, and seasonality were considered in the models to account for risk factors other than temperature and rainfall. Model selection and validation were performed using various statistical methods. Forecast precision was analyzed using cross-validation, Receiver Operating Characteristics curve, and root mean square errors. Finally, forecasts were translated into stratified dengue risk indices in time series formats.Results: Findings showed weekly mean temperature and cumulative rainfall preceded higher relative risk of dengue by 9-16 weeks and that a forecast with at least 3 months would provide sufficient time for mitigation in Singapore. Results showed possibility of predicting dengue cases 1-16 weeks using temperature and rainfall; whereas, consideration of autoregression and trend further enhance forecast precision. Sensitivity analysis showed the forecasting models could detect outbreak and non-outbreak at above 90% with less than 20% false positive. Forecasts were translated into stratified dengue risk indices using color codes and indices ranging from 1-10 in calendar or time sequence formats. Simplified risk indices interpreted forecast according to annual alert and outbreak thresholds; thus, provided uniform interpretation.Significance: A prediction model was developed that forecasted a prognosis of dengue up to 16 weeks in advance with sufficient accuracy. Such a prognosis can be used as an early warning to enhance evidence-based decision making and effective use of public health resources as well as improved effectiveness of dengue surveillance and control. Simple and clear dengue risk indices improve communications to stakeholders.
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- Hii, Yien Ling, et al.
(författare)
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Dengue risk index as an early warning
- 2013
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Introduction: A dengue early warning forewarns stakeholders and promotes timely prevention. Besides accuracy and timeliness, an effective early warning system must be comprised of a structure that allows clear and comprehensible communications to stakeholders, and facilitates planning of actions that corroborate with risks. To aid such communication and planning efforts, this study established a risk-stratified forecast strategy which relies on uniformly interpreted risk indices derived from forecasted dengue cases. Methodologies & Findings: We adopted the Poisson forecasting model developed by Hii et al. (2012) as model-1 and established a model-2 that considered only temperature and rainfall. We validate and compared the models for their forecast precision and sensitivity to diagnose outbreak and non-outbreak. Models were trained using data from 2001-2010. Forecast precision for the period 2011-2012 was analyzed using six cross-validations of 16-weeks forecast and root mean square errors. Operating Characteristic curve was used to analyze sensitivity of models. Forecasts were then translated into dengue risk indices according to estimated alert and epidemic thresholds. Results showed that model-1 and model-2 explained about 84% and 70% of variance in dengue distribution, respectively. Average RMSE was 28 for model-1 and 33 for model-2 during cross-validations. ROC area was 0.96 (CI=0.93-0.98) for model-1 and 0.92 (CI=0.88-0.96) for model-2 in 2004-2010. The two models were able to forecast outbreak about 90% accuracy with around 10% false positive in 2011-2012. Monthly and seasonal calendar risk index and weekly time series risk index were established using color scheme to represent risk levels. Significance: Translation of a forecast to dengue risk index permits rapid and clear interpretation of forecast; thus enhances the effectiveness of an early warning. Further studies on feasibility of developing an automated forecast-control-calibration-system using different forecasting methods to allow parallel forecast for comparison and monitoring will enhance sustainability of forecast precision.
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- Ingole, Vijendra, 1984-
(författare)
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Too Hot! : an Epidemiological Investigation of Weather-Related Mortality in Rural India
- 2016
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- BackgroundMost environmental epidemiological studies are conducted in high income settings. The association between ambient temperature and mortality has been studied worldwide, especially in developed countries. However, more research on the topic is necessary, particularly in India, given the limited evidence on the relationship between temperature and health in this country. The average global temperature is increasing, and it is estimated that it will go up further. The factors affecting vulnerability to heat-related mortality are not well studied. Therefore, identifying high-risk population subgroups is of particular importance given the rising temperature in India.ObjectivesThis research aimed to investigate the association of daily mean temperature and rainfall with daily deaths (Paper I), examine the relationship of hot and cold days with total and cause-specific mortality (Paper II), assess the effects of heat and cold on daily mortality among different socio-demographic groups (Paper III) and estimate the effect of maximum temperature on years of life lost (Paper IV).MethodsThe Vadu Health and Demographic Surveillance System (HDSS) monitors daily deaths, births, in-out migration and other demographic trends in 22 villages from two administrative blocks in the rural Pune district of Maharashtra state, in western India. Daily deaths from Vadu HDSS and daily weather data (temperature and rainfall) from the Indian Meteorological Department were collected from 2003 through 2013. Verbal autopsy data were used to define causes of death and classified into four groups: non-infectious diseases, infectious diseases, external causes and unspecified causes of death. Socio-demographic groups were based on education, occupation, house type and land ownership. In all papers, time series regression models were applied as the basic approach; additionally, in Paper III, a case-crossover design and, in Paper IV, a distributed lag non-linear model (DLNM) were used.ResultsThere was a significant association between daily temperature and mortality. Younger age groups (0-4 years) reported higher risk of mortality due to high and low temperature and heavy rainfall. In the working age group (20-59 years), mortality was significantly associated only with high temperature. Mortality due to non-infectious diseases was higher on hot days (>39°C), while mortality from infectious diseases and from external causes were not associated with hot or cold days. A higher heat-related total mortality was observed among men than in women. Mortality among residents with low education and those whose occupation was farming was associated with high temperature. We found a significant impact of high temperature on years of life lost, which confirms our results from the previous research (Papers I-III).ConclusionThe study findings broadened our knowledge of the health impacts of environmental exposure by providing evidence on the risks related to ambient temperature in a rural population in India. More specifically, the study identified vulnerable population groups (working age groups, those of low education and farmers) in relation to high temperature. The adverse effect of heat on population is preventable if local human and technical capacities for risk communication and promoting adaptive behavior are built. Furthermore, it is necessary to increase residents’ awareness and prevention measures to tackle this public health challenge in rural populations.
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- Kien, Tran Mai, et al.
(författare)
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Climate Services For Infectious Disease Control: A Nexus Between Public Health Preparedness and Sustainable Development, Lessons Learned From Long-Term Multi Site Time Series Analysis of Dengue Fever in Vietnam
- 2016
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Ingår i: International conference on public health: Accelerating the achievement of sustainable development goals for the improvement and equitable distribution of population health. ; , s. 83-84
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Background: Climate Services provide valuable information for making actionable, data-driven decisions to protect public health in a myriad of manners. There is mounting global evidence of the looming threat climate change poses to human health, including the variability and intensity of infectious disease outbreaks in Vietnam and other low-resource and developing areas. In light of the Sustainable Development Goals, lessons learned from time-series analysis may inform public health preparedness strategies for sustainable urban development in terms of dengue epidemiology, surveillance, control, and early warnings.Subjects and Methods: Nearly 40 years of spatial and temporal (times-series) dataset of meteorological records, including rainfall, temperature, and humidity (among others) which can be predictors of dengue were assembled for all provinces of Vietnam and associated with case data reported to General Department of Preventive Medicine, Ministry of Health of Vietnam during the same period. Time series of climate and disease variables was analyzed for trends and changing patterns of those variables over time. The time-series statistical analysis methods sought to identify spatial (when possible) and temporal trends, seasonality, cyclical patterns of disease, and to discover anomalous outbreak events, which departed from expected epidemiological patterns and corresponding meteorological phenomena, such as El Nino Southern Oscillation (ENSO).Results: Analysis yielded largely conserved finding with other locations in South East Asia for larger Outbreak years and events such as ENSO. Seasonality, trend, and cycle in many provinces were persistent throughout the dataset, indicating strong potential for Climate Services to be used in dengue early warnings.Conclusion: Even public health practitioners, having adequate tools for dengue control available must plan and budget vector control and patient treatment efforts well in advance of large scale dengue epidemics to curb such events overall morbidity and mortality. Similarly, urban and sustainable development in Vietnam might benefit from evidence linking climate change, and ill-health events spatially and temporally in future planning. Long term analysis of dengue case data and meteorological records, provided a cases study evidence for emerging opportunities that on how refined climate services could contribute to protection of public health.
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- Liu-Helmersson, Jing, 1960-
(författare)
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Climate Change, Dengue and Aedes Mosquitoes : Past Trends and Future Scenarios
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Background Climate change, global travel and trade have facilitated the spread of Aedes mosquitoes and have consequently enabled the diseases they transmit (dengue fever, Chikungunya, Zika and yellow fever) to emerge and re-emerge in uninfected areas. Large dengue outbreaks occurred in Athens in 1927 and in Portuguese island, Madeira in 2012, but there are almost no recent reports of Aedes aegypti, the principal vector, in Europe. A dengue outbreak needs four conditions: sufficient susceptible humans, abundant Aedes vector, dengue virus introduction, and conducive climate. Can Aedes aegypti establish themselves again in Europe in the near future if they are introduced? How do the current and future climate affect dengue transmission globally, and regionally as in Europe? This thesis tries to answer these questions.Methods Two process-based mathematical models were developed in this thesis. Model 1 describes a vector’s ability to transmit dengue – vectorial capacity – based on temperature and diurnal temperature range (DTR). Model 2 describes vector population dynamics based on the lifecycle of Aedes aegypti. From this model, vector abundance was estimated using both climate as a single driver, and climate together with human population and GDP as multiple drivers; vector population growth rate was derived as a threshold condition to estimate the vector’s invasion to a new place.Results Using vectorial capacity, we estimate dengue epidemic potential globally for Aedes aegypti and in Europe for Aedes aegypti and Aedes albopictus. We show that mean temperature and DTR are both important in modelling dengue transmission, especially in a temperate climate zone like Europe. Currently, South Europe is over the threshold for dengue epidemics if sufficient dengue vectors are present. Aedes aegypti is on the borderline of invasion into the southern tip of Europe. However, by end of this century, the invasion of Aedes aegypti may reach as far north as the middle of Europe under the business-as-usual climate scenario. Or it may be restricted to the south Europe from the middle of the century if the low carbon emission – Paris Agreement – is implemented to limit global warming to below 2°C.Conclusion Climate change will increase the area and time window for Aedes aegypti’s invasion and consequently the dengue epidemic potential globally, and in Europe in particular. Successfully achieving the Paris Agreement would considerably change the future risk scenario of a highly competent vector – Aedes aegypti’s – invasion into Europe. Therefore, the risk of transmission of dengue and other infectious diseases to the mainland of Europe depends largely on human efforts to mitigate climate change.
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- Liu-Helmersson, Jing, et al.
(författare)
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Seasonality of dengue epidemic potential in Europe - based on vectorial capacity for Aedes mosquitoes
- 2015
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Ingår i: Tropical medicine & international health. - : Wiley-Blackwell. - 1360-2276 .- 1365-3156. ; 20:Suppl. 1, s. 113-113
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Introduction: Dengue is a mosquito-borne viral infection that has become a major public health concern. About 390 million people are infected yearly. Increased global connectivity and population movement as well as climate change affect the global distribution of both dengue vectors and the virus, facilitating the spread of dengue to new geographic areas. Weather is an important factor determining mosquito behaviour and effectiveness of dengue virus transmission. Dengue epidemic potential depends on vectorial capacity of Aedes mosquitoes, which depend on climate, such as, temperature and diurnal temperature range. This study aims at identifying high-risk areas and high-risk time windows in Europe based on temperature, in order for timely vector surveillance and control.Methods: Relative vectorial capacity (rVc) was used to estimate dengue epidemic potential. Using historical and projected temperature data over two centuries (1901–2099) and temperature dependent vector parameters for Aedes vectors, rVc was calculated for 10 selected European cities from Stockholm in the North to Malaga in the South.Results: Compared to dengue endemic areas, rVc in Europe was lower and showed more prominent seasonality. The peak and width of the seasonal windows in rVc were generally higher in the South than the North. Currently, only South and Central-East Europe and the summer season corresponds to rVc that is over the threshold for possible dengue transmission. By the end of this century, in the best case scenario, all the Central and Southern European cities would be at risk for dengue transmission during the warmer months; in the worst case scenario, this risk would extend to Northern European to include Stockholm if dengue vectors were established and virus introduced.Conclusion: As travel and globalization become more frequent channels for dengue vector and virus introduction, Europe may face the reality of more frequent dengue outbreaks in their warmer months. Madeira's outbreak in 2012 underlines this concern. The future's high risk area and time window depend sensitively on climate scenarios. Therefore, it is important to emphasize climate change mitigation and enhance vector surveillance and control in Europe.Acknowledgement: This research was funded by the European Union 7th Framework Programme through 'DengueTools' (www.denguetools.net).Disclosure: Nothing to disclose.
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