| 1. |
- Näslund, Ulf, et al.
(författare)
-
Visualization of asymptomatic atherosclerotic disease for optimum cardiovascular prevention (VIPVIZA) : a pragmatic, open-label, randomised controlled trial
- 2019
-
Ingår i: The Lancet. - : Elsevier. - 0140-6736 .- 1474-547X. ; 393:10167, s. 133-142
-
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.
|
|
| 2. |
- Bowman, Leigh, et al.
(författare)
-
A comparison of Zika and dengue outbreaks using national surveillance data in the Dominican Republic
- 2018
-
Ingår i: PLoS Neglected Tropical Diseases. - : Public Library Science. - 1935-2727 .- 1935-2735. ; 12:11
-
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.
|
|
| 3. |
- Ingole, Vijendra, et al.
(författare)
-
Socioenvironmental factors associated with heat and cold-related mortality in Vadu HDSS, western India : a population-based case-crossover study
- 2017
-
Ingår i: International journal of biometeorology. - : Springer. - 0020-7128 .- 1432-1254. ; 61:10, s. 1797-1804
-
Tidskriftsartikel (refereegranskat)abstract
- Ambient temperatures (heat and cold) are associated with mortality, but limited research is available about groups most vulnerable to these effects in rural populations. We estimated the effects of heat and cold on daily mortality among different sociodemographic groups in the Vadu HDSS area, western India. We studied all deaths in the Vadu HDSS area during 2004-2013. A conditional logistic regression model in a case-crossover design was used. Separate analyses were carried out for summer and winter season. Odds ratios (OR) and 95% confidence intervals (CI) were estimated for total mortality and population subgroups. Temperature above a threshold of 31 A degrees C was associated with total mortality (OR 1.48, CI = 1.05-2.09) per 1 A degrees C increase in daily mean temperature. Odds ratios were higher among females (OR 1.93; CI = 1.07-3.47), those with low education (OR 1.65; CI = 1.00-2.75), those owing larger agricultural land (OR 2.18; CI = 0.99-4.79), and farmers (OR 1.70; CI = 1.02-2.81). In winter, per 1 A degrees C decrease in mean temperature, OR for total mortality was 1.06 (CI = 1.00-1.12) in lag 0-13 days. High risk of cold-related mortality was observed among people occupied in housework (OR = 1.09; CI = 1.00-1.19). Our study suggests that both heat and cold have an impact on mortality particularly heat, but also, to a smaller degree, cold have an impact. The effects may differ partly by sex, education, and occupation. These findings might have important policy implications in preventing heat and cold effects on particularly vulnerable groups of the rural populations in low and middle-income countries with hot semi-arid climate.
|
|
| 4. |
- Kien, Tran Mai, et al.
(författare)
-
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
-
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
-
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.
|
|
| 5. |
|
|
| 6. |
- Liyanage, Prasad, et al.
(författare)
-
Evaluation of intensified dengue control measures with interrupted time series analysis in the Panadura Medical Officer of Health division in Sri Lanka : a case study and cost-effectiveness analysis
- 2019
-
Ingår i: The Lancet Planetary Health. - : Elsevier. - 2542-5196. ; 3:5, s. e211-e218
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Dengue has become a major public health problem in Sri Lanka with a considerable economic burden. As a response, in June, 2014, the Ministry of Health initiated a proactive vector control programme in partnership with military and police forces, known as the Civil-Military Cooperation (CIMIC) programme, that was targeted at high-risk Medical Officer of Health (MOH) divisions in the country. Evaluating the effectiveness and cost-effectiveness of population-level interventions is essential to guide public health planning and resource allocation decisions, particularly in resource-limited health-care settings.Methods: Using an interrupted time series design with a non-linear extension, we evaluated the impact of vector control interventions from June 22, 2014, to Dec 29, 2016, in Panadura, a high-risk MOH division in Western Province, Sri Lanka. We used dengue notification and larval survey data to estimate the reduction in Breteau index and dengue incidence before and after the intervention using two separate models, adjusting for time-varying confounding variables (ie, rainfall, temperature, and the Oceanic Niño Index). We also assessed the cost and cost-effectiveness of the CIMIC programme from the perspective of the National Dengue Control Unit under the scenarios of different levels of hospitalisation of dengue cases (low [25%], medium [50%], and high [75%]) in terms of cost per disability-adjusted life-year averted (DALY).Findings: Vector control interventions had a significant impact on combined Breteau index (relative risk reduction 0·43, 95% CI 0·26 to 0·70) and on dengue incidence (0·43, 0·28 to 0·67), the latter becoming prominent 2 months after the intervention onset. The mean number of averted dengue cases was estimated at 2192 (95% CI 1741 to 2643), and the total cost of the CIMIC programme at 2016 US$271 615. Personnel costs accounted for about 89% of the total cost. In the base-case scenario of moderate level of hospitalisation, the CIMIC programme was cost-saving with a probability of 70% under both the lowest ($453) and highest ($1686) cost-effectiveness thresholds, resulting in a net saving of $20 247 (95% CI −57 266 to 97 790) and averting 176 DALYs (133 to 226), leading to a cost of −$98 (−497 to 395) per DALY averted. This was also the case for the scenario with high hospitalisation levels (cost per DALY averted −$512, 95% CI −872 to −115) but with a higher probability of 99%. In the scenario with low hospitalisation levels (cost per DALY averted $690, 143 to 1379), although the CIMIC programme was cost-ineffective at the lowest threshold with a probability of 77%, it was cost-effective at the highest threshold with a probability of 99%.Interpretation: This study suggests that communities affected by dengue can benefit from investments in vector control if interventions are implemented rigorously and coordinated well across sectors. By doing so, it is possible to reduce the disease and economic burden of dengue in endemic settings.Funding: None.
|
|
| 7. |
- Quam, Mikkel B., et al.
(författare)
-
Dissecting Japan's Dengue Outbreak in 2014
- 2016
-
Ingår i: American Journal of Tropical Medicine and Hygiene. - : American Society of Tropical Medicine and Hygiene. - 0002-9637 .- 1476-1645. ; 94:2, s. 409-412
-
Tidskriftsartikel (refereegranskat)abstract
- Despite Japan's temperate climate, a dengue outbreak occurred in Tokyo for the first time in over 70 years in 2014. We dissected this dengue outbreak based on phylogenetic analysis, travel interconnectivity, and environmental drivers for dengue epidemics. Comparing the available dengue virus 1 (DENV1) E gene sequence from this outbreak with 3,282 unique DENV1 sequences in National Center for Biotechnology Information suggested that the DENV might have been imported from China, Indonesia, Singapore, or Vietnam. With travelers arriving into Japan, Guangzhou (China) may have been the source of DENV introduction, given that Guangzhou also reported a large-scale dengue outbreak in 2014. Coinciding with the 2014 outbreak, Tokyo's climate conditions permitted the amplification of Aedes vectors and the annual peak of vectorial capacity. Given suitable vectors and climate conditions in addition to increasing interconnectivity with endemic areas of Asia, Tokyo's 2014 outbreak did not come as a surprise and may foretell more to come.
|
|
| 8. |
- Ramadona, Aditya Lia, et al.
(författare)
-
A combination of incidence data and mobility proxies from social media predicts the intra-urban spread of dengue in Yogyakarta, Indonesia
- 2019
-
Ingår i: PLoS Neglected Tropical Diseases. - : Public Library of Science (PLoS). - 1935-2727 .- 1935-2735. ; 13:4
-
Tidskriftsartikel (refereegranskat)abstract
- Only a few studies have investigated the potential of using geotagged social media data for predicting the patterns of spatio-temporal spread of vector-borne diseases. We herein demonstrated the role of human mobility in the intra-urban spread of dengue by weighting local incidence data with geo-tagged Twitter data as a proxy for human mobility across 45 neighborhoods in Yogyakarta city, Indonesia. To estimate the dengue virus importation pressure in each study neighborhood monthly, we developed an algorithm to estimate a dynamic mobility-weighted incidence index (MI), which quantifies the level of exposure to virus importation in any given neighborhood. Using a Bayesian spatio-temporal regression model, we estimated the coefficients and predictiveness of the MI index for lags up to 6 months. Specifically, we used a Poisson regression model with an unstructured spatial covariance matrix. We compared the predictability of the MI index to that of the dengue incidence rate over the preceding months in the same neighborhood (autocorrelation) and that of the mobility information alone. We based our estimates on a volume of 1·302·405 geotagged tweets (from 118·114 unique users) and monthly dengue incidence data for the 45 study neighborhoods in Yogyakarta city over the period from August 2016 to June 2018. The MI index, as a standalone variable, had the highest explanatory power for predicting dengue transmission risk in the study neighborhoods, with the greatest predictive ability at a 3-months lead time. The MI index was a better predictor of the dengue risk in a neighborhood than the recent transmission patterns in the same neighborhood, or just the mobility patterns between neighborhoods. Our results suggest that human mobility is an important driver of the spread of dengue within cities when combined with information on local circulation of the dengue virus. The geotagged Twitter data can provide important information on human mobility patterns to improve our understanding of the direction and the risk of spread of diseases, such as dengue. The proposed MI index together with traditional data sources can provide useful information for the development of more accurate and efficient early warning and response systems.
|
|
| 9. |
|
|
| 10. |
- Ramadona, Aditya Lia, et al.
(författare)
-
Validating search protocols for mining of health and disease events on Twitter
- 2016
-
Ingår i: International Conference on Public Health: Accelerating the achievment of sustainable development goals for the improvement and equitable distribution of population health. - 9786027148413 ; , s. 142-143
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- In the year of 2016, there were more than 24 million Indonesian twitter users sharing news, events, as well as personal feelings and experiences on Twitter. This study seeks to validate a search protocol of health-related terms using real-time Twitter data which can later be used to understand if, and how, twitter can reveal information on the current health situation in Indonesia. In this validation study of mining protocols, we extracted geo-located conversations related to health and disease postings on Twitter using a set of pre-defined keywords, assessed the prevalence, frequency and timing of such content in these conversations, and validated how this search protocol was able to detect relevant disease tweets.Groups of words and phrases relevant to disease symptoms and health outcomes were used in a protocol developed in the Indonesian language in order to extract relevant content from geo-tagged Twitter feeds. A supervised learning algorithm using Classification and Regression Trees was used to validate search protocols of disease and health hits comparing to those identified by a team of human experts. The experts categorized tweets as positive or negative in respect to health events. The model fit was evaluated based on prediction performance.We observed 390 tweets from historical Twitter feeds and 1,145,649 tweets from Twitter stream feeds during the period July 26th to August 1st, 2016. Only twitter hits with health related keywords in the Indonesian language were obtained. The accuracy of predictions of mined hits versus expert validated hits using the CART algorithm showed good validity with AUC beyond 0.8.Our study shows that monitoring of public sentiment on Twitter, combined with contextual knowledge about the disease, can detect health and disease tweets and potentially be used as a valuable real-time proxy for health events over space and time.
|
|
