| 1. |
- Ramadona, Aditya L., 1982-
(författare)
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Spatiotemporal prediction of arbovirus outbreak risk : the role of weather and population mobility
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Background: Arboviruses such as dengue and chikungunya have been a significant public health burden globally for several decades. In Indonesia, all four dengue serotypes are circulating. Considering that Indonesian children are exposed to dengue early in life, and secondary infection is more likely to cause severe dengue, the population of Indonesia is confronting a high potential risk of severe dengue. Severe complications such as hemorrhage can develop and lead to fatal outcomes. There exists no specific treatment for dengue infection, but symptomatic treatment can be effective to prevent deaths. Consequently, vector control has become a critical component for controlling dengue transmission, but it is currently often triggered as a reactive response to observed outbreak clusters. Based on disease surveillance, it thus remains challenging to implement vector control efficiently to prevent outbreaks. While meteorological conditions have shown to be predictive of dengue incidence over space and time, it has rarely been used to predict outbreaks at a fine-scale intra-urban level. Further, as the propagation of dengue outbreaks and the introduction of viruses has been found to be associated with human mobility, predictive models combining meteorological conditions with granular mobility data hold promise to provide more predictive models. The objectives in this thesis were to 1) describe the influence of temperature, rainfall, and past dengue cases, and population mobility on dengue risk; 2) develop and validate spatiotemporal models of dengue outbreak risk at fine-scale at the intra-urban level; 3) to utilize new data to assess the emergence and spread of chikungunya in an outbreak situation.Methods: Initially, multivariate time series regression models were established to analyze the risk of dengue corresponding to monthly mean temperature, cumulative rainfall, and past dengue case. Following that, we investigated the potential use of geotagged social media data as a proxy of population mobility to estimate the effect of dengue virus importation pressure in urban villages. Subsequently, we employed distributed lag non-linear models with a Spatiotemporal Bayesian hierarchical model framework to determine the exposure-lag-response association between the risk of dengue and meteorological data while allowing the spatial covariance to be informed by mobility flows. Finally, we validated the selected best-fitted model by its predictive ability using an unseen dataset to mimic an actual situation of an early warning system in use.Results: We found that an optimal combination of meteorology and autoregressive lag terms of past dengue cases was predictive of dengue incidence and the occurrence of dengue epidemics. Subsequently, when we integrated mobility data our results suggested that population mobility was an essential driver of the spread of dengue within cities when combined with information on the local circulation of the dengue virus. The geotagged Twitter data was found to provide important information on presumably local population mobility patterns which were predictive and can improve our understanding of the direction and the risk of spread.Conclusions: A spatiotemporal prediction model was developed that predicted a prognosis of dengueat fine spatial and temporal resolution. Subsequently, such a prognosis can be used as the foundation for developing an early warning system to more effectively deploy vector control prior to the establishment of local outbreak clusters. These findings have implications for targeting dengue control activities at the intraurban villages level, especially in the light of ever increasing population growth, mobility and climate change.
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| 2. |
- 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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| 3. |
- 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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| 4. |
- 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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| 5. |
- Santosa, Ailiana, 1976-
(författare)
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Where are the world’s disease patterns heading? : The challenges of epidemiological transition
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- INTRODUCTION: Epidemiological transition theory, first postulated by Omran in 1971, provides a useful framework for understanding cause-specific mortality changes and may contribute usefully to predictions about cause-specific mortality. However, understandings of mortality transitions and associated epidemiological changes remain poorly defined for public health practitioners due to lack of evidence from low- and middle-income countries. Therefore, understanding of the concept and development of epidemiological transition theory as well as population burden of premature mortality attributable to risk factors is needed.OBJECTIVES: This thesis aims to understand how epidemiological transition theory has been applied in different contexts, using available evidence on mortality transitions from high, middle- and low- income countries, as well as the contribution of risk factors to mortality transitions, particularly for premature mortality.METHODS: A Medline literature search from 1971 to 2013 was conducted to synthesise published evidence on mortality transition (paper I). A descriptive analysis of trends in cause of death using INDEPTH data was conducted, focusing on specific causes of death in 12 INDEPTH sites in Africa and Asia, using the INDEPTH 2013 standard population structure for appropriate comparisons across sites (paper II). A retrospective dynamic cohort database was constructed from Swedish population registers for the age range 30-69 years during 1991-2006, to measure reductions in premature non-communicable disease mortality using a life table method (paper III). Prospective cohort data from Västerbotten Intervention Programme from 1990 to 2006 were used to measure the magnitude of premature non-communicable disease mortality reductions associated with risk factor changes for each period of time (paper IV).FINDINGS: There were changes in emphasis in research on epidemiological transition over the four decades from 1971 to 2013, from cause of death to wide-ranging aspects of the determinants of mortality with increasing research interests in low-and middle-income countries, with some unconsidered aspects of social determinants contributing to deviations from classic theoretical pathways. Mortality rates declined in most sites, with the annual reductions in premature adult mortality varied across INDEPTH sites, Sweden, which now is at late stage of epidemiological transition stage, achieved a 25% reduction in premature mortality during 1991-2006. Overall downward trends in risk factors have helped to reduce premature mortality in the population of Västerbotten County, but some benefits were offset by other increasing risks. The largest mortality changes accrued from reductions in smoking, hypertension and hypercholesterolaemia.CONCLUSIONS: This thesis established patterns of current epidemiological transition in high, middle-and low-income countries (Asia and Africa), where the theory fits the transition patterns in some countries, but with some needs for further adjustments in other settings, as well as deviations from the classical ET theory in the last four decades. It highlights the need to identify the burden of mortality and morbidity, particularly for reducing mortality occurring before the age of 70 years and its attribution to risk factors, which are a major public health challenge. This informs shifting of public health priorities and resources towards prevention and control of chronic non-communicable disease risk factors.
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| 6. |
- 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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| 7. |
- Liyanage, Prasad, 1975-
(författare)
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The Influence of Climate and Public Health Interventions on Aedes Vectors and Dengue in Sri Lanka
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Introduction: Dengue, a viral infection transmitted by Aedes mosquitos, flourishes in urban tropical environments by a complex process. Interactions among susceptible humans, dengue viruses, and Aedes mosquitoes determine dengue transmission patterns, and these interactions are modified by driving factors related to weather, the environment, and human behaviour, including mobility. Understanding the drivers of dengue and evaluating the effectiveness and costeffectiveness of existing vector control policies are vital to developing evidence-based and timely interventions.Methods: The exposure-lag-response associations between weather variables, Aedes vector indices and dengue at each sub-district Medical Officer of Health (MOH) divisions in Kalutara district, Sri Lanka, were estimated using distributed lag non-linear models. These estimates were meta-analyzed to obtain the average estimates for the district, while exploring the heterogeneities among MOH divisions. Non-linear extension to the interrupted time series analysis was used to evaluate the impact of nation wide mobility restrictions implemented during COVID-19 pandemic on dengue risk at each district, at different age groups in the western province and at the climate zones in Sir Lanka. The effects of the vector control interventions implemented through the civil military cooporation (CIMIC) on dengue were estimated at Panadura MOH division of Kalutara district using interrupted time series analysis while adjusting for potential confounders. The costeffectiveness of the CIMIC intervention was evaluated using a decision analytical modelling framework.Results: We found that El Niño, rainfall, temperature and Aedes larval indices were associated with each other, and dengue, at lag intervals expanding from one to six months. The nation wide mobility restriction was associated with a statistically significant reduction in dengue risk in all climate zones in Sri Lanka. The highest impact was observed among the children age less than 19 years. We found that the CIMIC intervention reduced dengue risk by 50% and was cost-effectivein a defined area.Conclusion: The manifestation of dengue is preceded by the biologically plausible latencies of increasing Aedes larvae and the onset of weather events in Kalutara district. When augmented with location-specific information of vector activities, one to six months lead time from the onset of weather events enables public health authorities to set up short, intermediate, and long-term goals for vector control interventions. The observed significant reduction in dengue risk following the national lockdown in Sri Lanka further highlighted the importance of vector control at public places and schools. The findings of these studies suggest that communities affected by dengue can benefit from investments in vector control if interventions are implemented rigorously and coordinated well across sectors. The methodological framework we developed in this doctoral thesis will contribute to the understanding of the local determinants of dengue and the developmentof early warning systems blended with effective and cost-effective vector control interventions in Sri Lanka and beyond.
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| 8. |
- Muindi, Kanyiva, 1973-
(författare)
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Air pollution in Nairobi slums : sources, levels and lay perceptions
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- BackgroundAir quality in Africa has remained a relatively under-researched field. Most of the African population is dependent on biomass for cooking and heating, with most of the combustion happening in low efficiency stoves in unvented kitchens. The resulting high emissions are compounded by ingress from poor outdoor air in a context of poor emissions controls. The situation is dire in slum households where homes are crowded and space is limited, pushing households to cook in the same room that is used for sleeping. This study assessed the levels of particulate matter with aerodynamic diameter £ 2.5 microns (PM2.5) in slum households and people's perceptions of and attitudes towards air pollution and health risks of exposure in two slum areas, Viwandani and Korogocho, in the Nairobi city.Methods The study employed both qualitative and quantitative methods. For the quantitative study, we used structured questionnaires to collect data about the source of air pollution among adults aged 18 years and above and pregnant women residing in the two study communities. We used the DustTrak™ air samplers to monitor the indoor PM2.5 levels in selected households. We also collected data on community perceptions on air pollution, annoyance and associated health risks. We presented hotspot maps to portray the spatial distribution of perceptions on air pollution in the study areas. For the qualitative study, we conducted focus group discussions with adult community members. Groups were disaggregated by age to account for different languages used to communicate with the younger and older people. We analysed the qualitative data using thematic analysis.Results Household levels of PM2.5 varied widely across households and ranged from 1 to 12,369μg/m3 (SD=287.11). The household levels of PM2.5 levels were likely to exceed the WHO guidelines given the high levels observed in less than 24 hours of monitoring periods (on average 10.4 hours in Viwandani and 11.8 hours in Korogocho). Most of the respondents did not use ventilation use in the evening which coincided with the use of cookstove and lamp, mostly burning kerosene. The levels of PM2.5 varied by the type of fuels, with the highest emissions in households using kerosene for cooking and lighting. The PM2.5 levels spiked in the evenings and during periods of cooking using charcoal/wood. Despite these high levels, residents perceived indoor air to be less polluted compared with the outdoor air, possibly due to the presence of large sources of emissions near the communities such as dumpsites and industries. The community had mixed perceptions on the health impacts of air pollution, with respiratory illnesses perceived as the main consequence while vector or sanitation related diseases such as diarrhoea was also perceived to be related to air pollution.ConclusionsWith poor housing and reliance on dirty fuels, households in slums face potentially high levels of exposure to PM2.5 with dire implications on health. To address the poor perception on air pollution and knowledge gaps on the health effects of air pollution, education programs need to be developed and tailored. These programs should aim to provide residents with information on air quality and its impact on the health; what they can do as communities as well as empower them to reach out to government/stakeholders for action on outdoor sources of pollution such as emissions from dumpsites or industries. The government has a larger role in addressing some of the key pollution sources through policy formulation and strong implementation/enforcement.
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| 9. |
- Kriit, Hedi Katre, 1990-
(författare)
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Improved health economic assessments of sustainable transport solutions in urban environments
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Introduction: Part of the European Strategy to achieve climate neutrality in the transport sector is to increase the proportion of electric vehicles (EVs) and active commuting. Health co-benefits from reduced air pollution and increased active commuting are assumed to follow; however, all dimensions of expected health effects are not quantified nor valued monetarily. Current state-of-the art health impact assessments (HIAs) of air pollution assume immediate change in health with exposure; however, the time-window of importance for health outcomes is unknown. Moreover, the currently applied risk estimate of sick leaves in relation to air pollution is poorly generalizable due to outdated exposure assessment and subjective data on outcome. The overall aim of this thesis is to assess the health economic effects of sustainable urban transport solutions and improve the epidemiological knowledge base of air pollution effects. Methods: The health effects of increased active commuting and the resulting change in air pollution exposure were valued monetarily from a health care perspective, and a cost-effectiveness analysis of investment in bicycle infrastructure was conducted. A health economic assessment from a societal perspective was also conducted for an increased proportion of EVs in the vehicle fleet, considering a change in both exhaust and non-exhaust particles. The exposure-lag response between air pollution and risk for ischemic heart disease (IHD) and stroke was assessed in a multi-cohort study using distributed lag-nonlinear models (DLNMs). A case cross-over study design was applied to estimate the odds of sick leaves in relation to short-term PM2.5 exposure, and production losses were valued using the human capital method. Results: Investing in bicycle infrastructure to enable increased active commuting was estimated to be cost-effective from a health care perspective. An increased proportion of EVs was estimated to decrease population-weighted PM2.5 concentrations without the use of studded winter tires, but was estimated to increase with the current use of studded winter tires in Stockholm Sweden. For a 0-50% use of studded winter tires the health economic costs ranged between €20 and €122 million (M). An independent effect of PM2.5 on sick leaves was estimated to correspond to €2M per year in productivity loss for the population of Stockholm municipality. Exposure time windows closer in time and local sources of air pollution were suggested to be of greater importance for incident IHD and stroke.Conclusions: This thesis has demonstrated the health economic potential in policies seeking to transform the transport sector towards sustainability. Investment in the transport sector could lead to decreased morbidity and decreased monetary burden in the health care sector. Non-exhaust particles should be considered in order to fully assess the health economic effects of EVs. Moreover, the risk estimate of sick leaves in relation to air pollution exposure could be included in international HIAs.
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| 10. |
- Sewe, Maquins Odhiambo, 1981-
(författare)
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Towards Climate Based Early Warning and Response Systems for Malaria
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Background: Great strides have been made in combating malaria, however, the indicators in sub Saharan Africa still do not show promise for elimination in the near future as malaria infections still result in high morbidity and mortality among children. The abundance of the malaria-transmitting mosquito vectors in these regions are driven by climate suitability. In order to achieve malaria elimination by 2030, strengthening of surveillance systems have been advocated. Based on malaria surveillance and climate monitoring, forecasting models may be developed for early warnings. Therefore, in this thesis, we strived to illustrate the use malaria surveillance and climate data for policy and decision making by assessing the association between weather variability (from ground and remote sensing sources) and malaria mortality, and by building malaria admission forecasting models. We further propose an economic framework for integrating forecasts into operational surveillance system for evidence based decisionmaking and resource allocation. Methods: The studies were based in Asembo, Gem and Karemo areas of the KEMRI/CDC Health and Demographic Surveillance System in Western Kenya. Lagged association of rainfall and temperature with malaria mortality was modeled using general additive models, while distributed lag non-linear models were used to explore relationship between remote sensing variables, land surface temperature(LST), normalized difference vegetation index(NDVI) and rainfall on weekly malaria mortality. General additive models, with and without boosting, were used to develop malaria admissions forecasting models for lead times one to three months. We developed a framework for incorporating forecast output into economic evaluation of response strategies at different lead times including uncertainties. The forecast output could either be an alert based on a threshold, or absolute predicted cases. In both situations, interventions at each lead time could be evaluated by the derived net benefit function and uncertainty incorporated by simulation. Results: We found that the environmental factors correlated with malaria mortality with varying latencies. In the first paper, where we used ground weather data, the effect of mean temperature was significant from lag of 9 weeks, with risks higher for mean temperatures above 250C. The effect of cumulative precipitation was delayed and began from 5 weeks. Weekly total rainfall of more than 120 mm resulted in increased risk for mortality. In the second paper, using remotely sensed data, the effect of precipitation was consistent in the three areas, with increasing effect with weekly total rainfall of over 40 mm, and then declined at 80 mm of weekly rainfall. NDVI below 0.4 increased the risk of malaria mortality, while day LST above 350C increased the risk of malaria mortality with shorter lags for high LST weeks. The lag effect of precipitation was more delayed for precipitation values below 20 mm starting at week 5 while shorter lag effect for higher precipitation weeks. The effect of higher NDVI values above 0.4 were more delayed and protective while shorter lag effect for NDVI below 0.4. For all the lead times, in the malaria admissions forecasting modelling in the third paper, the boosted regression models provided better prediction accuracy. The economic framework in the fourth paper presented a probability function of the net benefit of response measures, where the best response at particular lead time corresponded to the one with the highest probability, and absolute value, of a net benefit surplus. Conclusion: We have shown that lagged relationship between environmental variables and malaria health outcomes follow the expected biological mechanism, where presentation of cases follow the onset of specific weather conditions and climate variability. This relationship guided the development of predictive models showcased with the malaria admissions model. Further, we developed an economic framework connecting the forecasts to response measures in situations with considerable uncertainties. Thus, the thesis work has contributed to several important components of early warning systems including risk assessment; utilizing surveillance data for prediction; and a method to identifying cost-effective response strategies. We recommend economic evaluation becomes standard in implementation of early warning system to guide long-term sustainability of such health protection programs.
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