| 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. |
- 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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| 3. |
- 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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| 4. |
- Näslund, Ulf, et al.
(författare)
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Visualization of asymptomatic atherosclerotic disease for optimum cardiovascular prevention (VIPVIZA) : a pragmatic, open-label, randomised controlled trial
- 2019
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Ingår i: The Lancet. - : Elsevier. - 0140-6736 .- 1474-547X. ; 393:10167, s. 133-142
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Primary prevention of cardiovascular disease often fails because of poor adherence among practitioners and individuals to prevention guidelines. We aimed to investigate whether ultrasound-based pictorial information about subclinical carotid atherosclerosis, targeting both primary care physicians and individuals, improves prevention.METHODS: Visualization of asymptomatic atherosclerotic disease for optimum cardiovascular prevention (VIPVIZA) is a pragmatic, open-label, randomised controlled trial that was integrated within the Västerbotten Intervention Programme, an ongoing population-based cardiovascular disease prevention programme in northern Sweden. Individuals aged 40, 50, or 60 years with one or more conventional risk factors were eligible to participate. Participants underwent clinical examination, blood sampling, and ultrasound assessment of carotid intima media wall thickness and plaque formation. Participants were randomly assigned 1:1 with a computer-generated randomisation list to an intervention group (pictorial representation of carotid ultrasound plus a nurse phone call to confirm understanding) or a control group (not informed). The primary outcomes, Framingham risk score (FRS) and European systematic coronary risk evaluation (SCORE), were assessed after 1 year among participants who were followed up. This study is registered with ClinicalTrials.gov, number NCT01849575.FINDINGS: 3532 individuals were enrolled between April 29, 2013, and June 7, 2016, of which 1783 were randomly assigned to the control group and 1749 were assigned to the intervention group. 3175 participants completed the 1-year follow-up. At the 1-year follow-up, FRS and SCORE differed significantly between groups (FRS 1·07 [95% CI 0·11 to 2·03, p=0·0017] and SCORE 0·16 [0·02 to 0·30, p=0·0010]). FRS decreased from baseline to the 1-year follow-up in the intervention group and increased in the control group (-0·58 [95% CI -0·86 to -0·30] vs 0·35 [0·08 to 0·63]). SCORE increased in both groups (0·13 [95% CI 0·09 to 0·18] vs 0·27 [0·23 to 0·30]).INTERPRETATION: This study provides evidence of the contributory role of pictorial presentation of silent atherosclerosis for prevention of cardiovascular disease. It supports further development of methods to reduce the major problem of low adherence to medication and lifestyle modification.
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| 5. |
- Altmejd, Adam, et al.
(författare)
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Nowcasting COVID-19 statistics reported with delay : A case-study of Sweden and the UK
- 2023
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Ingår i: International Journal of Environmental Research and Public Health. - : MDPI. - 1661-7827 .- 1660-4601. ; 20:4
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Tidskriftsartikel (refereegranskat)abstract
- The COVID-19 pandemic has demonstrated the importance of unbiased, real-time statistics of trends in disease events in order to achieve an effective response. Because of reporting delays, real-time statistics frequently underestimate the total number of infections, hospitalizations and deaths. When studied by event date, such delays also risk creating an illusion of a downward trend. Here, we describe a statistical methodology for predicting true daily quantities and their uncertainty, estimated using historical reporting delays. The methodology takes into account the observed distribution pattern of the lag. It is derived from the "removal method"-a well-established estimation framework in the field of ecology.
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| 6. |
- Armando, Chaibo Jose, et al.
(författare)
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Climate variability, socio-economic conditions and vulnerability to malaria infections in Mozambique 2016–2018 : a spatial temporal analysis
- 2023
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Ingår i: Frontiers In Public Health. - : Frontiers Media S.A.. - 2296-2565. ; 11
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Tidskriftsartikel (refereegranskat)abstract
- Background: Temperature, precipitation, relative humidity (RH), and Normalized Different Vegetation Index (NDVI), influence malaria transmission dynamics. However, an understanding of interactions between socioeconomic indicators, environmental factors and malaria incidence can help design interventions to alleviate the high burden of malaria infections on vulnerable populations. Our study thus aimed to investigate the socioeconomic and climatological factors influencing spatial and temporal variability of malaria infections in Mozambique.Methods: We used monthly malaria cases from 2016 to 2018 at the district level. We developed an hierarchical spatial–temporal model in a Bayesian framework. Monthly malaria cases were assumed to follow a negative binomial distribution. We used integrated nested Laplace approximation (INLA) in R for Bayesian inference and distributed lag nonlinear modeling (DLNM) framework to explore exposure-response relationships between climate variables and risk of malaria infection in Mozambique, while adjusting for socioeconomic factors.Results: A total of 19,948,295 malaria cases were reported between 2016 and 2018 in Mozambique. Malaria risk increased with higher monthly mean temperatures between 20 and 29°C, at mean temperature of 25°C, the risk of malaria was 3.45 times higher (RR 3.45 [95%CI: 2.37–5.03]). Malaria risk was greatest for NDVI above 0.22. The risk of malaria was 1.34 times higher (1.34 [1.01–1.79]) at monthly RH of 55%. Malaria risk reduced by 26.1%, for total monthly precipitation of 480 mm (0.739 [95%CI: 0.61–0.90]) at lag 2 months, while for lower total monthly precipitation of 10 mm, the risk of malaria was 1.87 times higher (1.87 [1.30–2.69]). After adjusting for climate variables, having lower level of education significantly increased malaria risk (1.034 [1.014–1.054]) and having electricity (0.979 [0.967–0.992]) and sharing toilet facilities (0.957 [0.924–0.991]) significantly reduced malaria risk.Conclusion: Our current study identified lag patterns and association between climate variables and malaria incidence in Mozambique. Extremes in climate variables were associated with an increased risk of malaria transmission, peaks in transmission were varied. Our findings provide insights for designing early warning, prevention, and control strategies to minimize seasonal malaria surges and associated infections in Mozambique a region where Malaria causes substantial burden from illness and deaths.
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| 7. |
- Bowman, Leigh, et al.
(författare)
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A comparison of Zika and dengue outbreaks using national surveillance data in the Dominican Republic
- 2018
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Ingår i: PLoS Neglected Tropical Diseases. - : Public Library Science. - 1935-2727 .- 1935-2735. ; 12:11
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Aedes-borne arboviruses continue to precipitate epidemics worldwide. In Dominican Republic, the appearance of Zika virus cases that closely followed a large dengue epidemic provided an opportunity to study the different transmission drivers behind these two flaviviruses. Retrospective datasets were used to collect information on the populations at risk and descriptive statistics were used to describe the outbreaks on a national scale.METHODOLOGY/ PRINCIPAL FINDINGS: Expectedly, box plots showed that 75% of dengue was reported in those aged <20 years while Zika infections were more widely dispersed among the population. Dengue attack rates were marginally higher among males at 25.9 per 10,000 population vs. 21.5 per 10,000 population for females. Zika infections appeared to be highly clustered among females (73.8% (95% CI 72.6%, 75.0%; p<0.05)); age-adjusted Zika attack rates among females were 7.64 per 10,000 population compared with 2.72 per 10,000 population among males. R0 calculations stratified by sex also showed a significantly higher metric among females: 1.84 (1.82, 1.87; p<0.05) when compared to males at 1.72 (1.69, 1.75; p<0.05). However, GBS attack rates stratified by sex revealed slightly higher risk in males vs. females, at 0.62 and 0.57 per 10,000 population respectively.CONCLUSIONS/ SIGNIFICANCE: Evidence suggests little impact of existing dengue immunity on reported attack rates of Zika at the population level. Confounding of R0 and incident risk calculations by sex-specific over-reporting can alter the reliability of epidemiological metrics, which could be addressed using associated proxy syndromes or conditions to explore seemingly sex-skewed incidence. The findings indicate that community awareness campaigns, through influencing short-term health seeking behaviour, remain the most plausible mechanism behind increased reporting among women of reproductive age, although biological susceptibility cannot yet be ruled out. Media campaigns and screening are therefore recommended for women of reproductive age during Zika outbreaks. Future research should focus on clinical Zika outcomes among dengue seropositive individuals.
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| 8. |
- Brännström, Åke, 1975-, et al.
(författare)
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A Method for Estimating the Number of Infections From the Reported Number of Deaths
- 2022
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Ingår i: Frontiers In Public Health. - : Frontiers Media S.A.. - 2296-2565. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- At the outset of an epidemic, available case data typically underestimate the total number of infections due to insufficient testing, potentially hampering public responses. Here, we present a method for statistically estimating the true number of cases with confidence intervals from the reported number of deaths and estimates of the infection fatality ratio; assuming that the time from infection to death follows a known distribution. While the method is applicable to any epidemic with a significant mortality rate, we exemplify the method by applying it to COVID-19. Our findings indicate that the number of unreported COVID-19 infections in March 2020 was likely to be at least one order of magnitude higher than the reported cases, with the degree of underestimation among the countries considered being particularly high in the United Kingdom.
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| 9. |
- Colon-Gonzalez, J. Felipe, et al.
(författare)
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Projecting the risk of mosquito-borne diseases in a warmer and more populated world : a multi-model, multi-scenario intercomparison modelling study
- 2021
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Ingår i: The Lancet Planetary Health. - : Elsevier. - 2542-5196. ; 5:7, s. E404-E414
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Tidskriftsartikel (refereegranskat)abstract
- Background: Mosquito-borne diseases are expanding their range, and re-emerging in areas where they had subsided for decades. The extent to which climate change influences the transmission suitability and population at risk of mosquito-borne diseases across different altitudes and population densities has not been investigated. The aim of this study was to quantify the extent to which climate change will influence the length of the transmission season and estimate the population at risk of mosquito-borne diseases in the future, given different population densities across an altitudinal gradient.Methods: Using a multi-model multi-scenario framework, we estimated changes in the length of the transmission season and global population at risk of malaria and dengue for different altitudes and population densities for the period 1951-99. We generated projections from six mosquito-borne disease models, driven by four global circulation models, using four representative concentration pathways, and three shared socioeconomic pathways.Findings: We show that malaria suitability will increase by 1·6 additional months (mean 0·5, SE 0·03) in tropical highlands in the African region, the Eastern Mediterranean region, and the region of the Americas. Dengue suitability will increase in lowlands in the Western Pacific region and the Eastern Mediterranean region by 4·0 additional months (mean 1·7, SE 0·2). Increases in the climatic suitability of both diseases will be greater in rural areas than in urban areas. The epidemic belt for both diseases will expand towards temperate areas. The population at risk of both diseases might increase by up to 4·7 additional billion people by 2070 relative to 1970-99, particularly in lowlands and urban areas.Interpretation: Rising global mean temperature will increase the climatic suitability of both diseases particularly in already endemic areas. The predicted expansion towards higher altitudes and temperate regions suggests that outbreaks can occur in areas where people might be immunologically naive and public health systems unprepared. The population at risk of malaria and dengue will be higher in densely populated urban areas in the WHO African region, South-East Asia region, and the region of the Americas, although we did not account for urban-heat island effects, which can further alter the risk of disease transmission.
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| 10. |
- DiSera, Laurel, et al.
(författare)
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The Mosquito, the Virus, the Climate : An Unforeseen Réunion in 2018
- 2020
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Ingår i: GeoHealth. - : John Wiley & Sons. - 2471-1403. ; 4:8
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Tidskriftsartikel (refereegranskat)abstract
- The 2018 outbreak of dengue in the French overseas department of Réunion was unprecedented in size and spread across the island. This research focuses on the cause of the outbreak, asserting that climate played a large role in the proliferation of the Aedes albopictus mosquitoes, which transmitted the disease, and led to the dengue outbreak in early 2018. A stage‐structured model was run using observed temperature and rainfall data to simulate the life cycle and abundance of the Ae. albopictus mosquito. Further, the model was forced with bias‐corrected subseasonal forecasts to determine if the event could have been forecast up to 4 weeks in advance. With unseasonably warm temperatures remaining above 25°C, along with large tropical‐cyclone‐related rainfall events accumulating 10–15 mm per event, the modeled Ae. albopictus mosquito abundance did not decrease during the second half of 2017, contrary to the normal behavior, likely contributing to the large dengue outbreak in early 2018. Although subseasonal forecasts of rainfall for the December–January period in Réunion are skillful up to 4 weeks in advance, the outbreak could only have been forecast 2 weeks in advance, which along with seasonal forecast information could have provided enough time to enhance preparedness measures. Our research demonstrates the potential of using state‐of‐the‐art subseasonal climate forecasts to produce actionable subseasonal dengue predictions. To the best of the authors' knowledge, this is the first time subseasonal forecasts have been used this way.
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