| 1. |
- Ramadona, Aditya Lia, et al.
(författare)
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Prediction of Dengue Outbreaks Based on Disease Surveillance and Meteorological Data
- 2016
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 11:3
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Tidskriftsartikel (refereegranskat)abstract
- Research is needed to create early warnings of dengue outbreaks to inform stakeholders and control the disease. This analysis composes of a comparative set of prediction models including only meteorological variables; only lag variables of disease surveillance; as well as combinations of meteorological and lag disease surveillance variables. Generalized linear regression models were used to fit relationships between the predictor variables and the dengue surveillance data as outcome variable on the basis of data from 2001 to 2010. Data from 2011 to 2013 were used for external validation purposed of prediction accuracy of the model. Model fit were evaluated based on prediction performance in terms of detecting epidemics, and for number of predicted cases according to RMSE and SRMSE, as well as AIC. An optimal combination of meteorology and autoregressive lag terms of dengue counts in the past were identified best in predicting dengue incidence and the occurrence of dengue epidemics. Past data on disease surveillance, as predictor alone, visually gave reasonably accurate results for outbreak periods, but not for non-outbreaks periods. A combination of surveillance and meteorological data including lag patterns up to a few years in the past showed most predictive of dengue incidence and occurrence in Yogyakarta, Indonesia. The external validation showed poorer results than the internal validation, but still showed skill in detecting outbreaks up to two months ahead. Prior studies support the fact that past meteorology and surveillance data can be predictive of dengue. However, to a less extent has prior research shown how the longer-term past disease incidence data, up to years, can play a role in predicting outbreaks in the coming years, possibly indicating cross-immunity status of the population.
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| 2. |
- 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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| 3. |
- Ramadona, Aditya Lia, et al.
(författare)
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Validating search protocols for mining of health and disease events on Twitter
- 2016
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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
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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.
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| 4. |
- Schröders, Julia, et al.
(författare)
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How is Indonesia coping with its epidemic of chronic noncommunicable diseases? : A systematic review with meta-analysis
- 2017
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Ingår i: PLOS ONE. - : Public Library Science. - 1932-6203. ; 12:6
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Chronic noncommunicable diseases (NCDs) have emerged as a huge global health problem in low- and middle-income countries. The magnitude of the rise of NCDs is particularly visible in Southeast Asia where limited resources have been used to address this rising epidemic, as in the case of Indonesia. Robust evidence to measure growing NCD-related burdens at national and local levels and to aid national discussion on social determinants of health and intra-country inequalities is needed. The aim of this review is (i) to illustrate the burden of risk factors, morbidity, disability, and mortality related to NCDs; (ii) to identify existing policy and community interventions, including disease prevention and management strategies; and (iii) to investigate how and why an inequitable distribution of this burden can be explained in terms of the social determinants of health.METHODS: Our review followed the PRISMA guidelines for identifying, screening, and checking the eligibility and quality of relevant literature. We systematically searched electronic databases and gray literature for English- and Indonesian-language studies published between Jan 1, 2000 and October 1, 2015. We synthesized included studies in the form of a narrative synthesis and where possible meta-analyzed their data.RESULTS: On the basis of deductive qualitative content analysis, 130 included citations were grouped into seven topic areas: risk factors; morbidity; disability; mortality; disease management; interventions and prevention; and social determinants of health. A quantitative synthesis meta-analyzed a subset of studies related to the risk factors smoking, obesity, and hypertension.CONCLUSIONS: Our findings echo the urgent need to expand routine risk factor surveillance and outcome monitoring and to integrate these into one national health information system. There is a stringent necessity to reorient and enhance health system responses to offer effective, realistic, and affordable ways to prevent and control NCDs through cost-effective interventions and a more structured approach to the delivery of high-quality primary care and equitable prevention and treatment strategies. Research on social determinants of health and policy-relevant research need to be expanded and strengthened to the extent that a reduction of the total NCD burden and inequalities therein should be treated as related and mutually reinforcing priorities.
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| 5. |
- Schröders, Julia, et al.
(författare)
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Millennium Development Goal Four and Child Health Inequities in Indonesia : A Systematic Review of the Literature
- 2015
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 10:5
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Forskningsöversikt (refereegranskat)abstract
- Introduction Millennium Development Goal (MDG) 4 calls for reducing mortality of children under-five years by two-thirds by 2015. Indonesia is on track to officially meet the MDG 4 targets by 2015 but progress has been far from universal. It has been argued that national level statistics, on which MDG 4 relies, obscure persistent health inequities within the country. Particularly inequities in child health are a major global public health challenge both for achieving MDG 4 in 2015 and beyond. This review aims to map out the situation of MDG 4 with respect to disadvantaged populations in Indonesia applying the Social Determinants of Health (SDH) framework. The specific objectives are to answer: Who are the disadvantaged populations? Where do they live? And why and how is the inequitable distribution of health explained in terms of the SDH framework?Methods and Findings We retrieved studies through a systematic review of peer-reviewed and gray literature published in 1995-2014. The PRISMA-Equity 2012 statement was adapted to guide the methods of this review. The dependent variables were MDG 4-related indicators; the independent variable "disadvantaged populations" was defined by different categories of social differentiation using PROGRESS. Included texts were analyzed following the guidelines for deductive content analysis operationalized on the basis of the SDH framework. We identified 83 studies establishing evidence on more than 40 different determinants hindering an equitable distribution of child health in Indonesia. The most prominent determinants arise from the shortcomings within the rural health care system, the repercussions of food poverty coupled with low health literacy among parents, the impact of low household decision-making power of mothers, and the consequences of high persistent use of traditional birth attendants among ethnic minorities.Conclusion This review calls for enhanced understanding of the determinants and pathways that create, detain, and overcome inequities in child health in resource constraint settings like Indonesia and the promotion of actionable health policy recommendations and tailored investments.
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| 6. |
- Thomsen, Sarah, et al.
(författare)
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The world we want : focus on the most disadvantaged
- 2013
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Ingår i: Global Health Action. - : Informa UK Limited. - 1654-9716 .- 1654-9880. ; 6, s. 20919-
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- The global commitment to the Millennium Development Goal (MDG) process has resulted in significant, positive changes in health-related MDGs on the global and country levels since 1990. However, while overall progress has been made, gaps in achievements between and within many countries have not decreased, with the poorest and most disadvantaged communities being the least likely to have benefitted. This is particularly the case in many emerging economies where the gap between the rich and poor, educated and uneducated, and minority and majority ethnic populations is actually increasing. For example, in India, where the Gross National Income in purchasing power parity in 2010 was $3,468, use of antenatal care services increased by 12% from 1996 to 2008, but only 0.1% among the poor. In Indonesia, infant mortality rates are on the decline in all regions of the country except for the Eastern regions where they remain high. In Vietnam, inequity in home deliveries between poor, rural Kinh (majority) and minority mothers has increased in the last 5 years during a period of rapid economic growth. In urban China, domestic rural-to-urban migrants account for a significant proportion of notified cases of infectious diseases such as tuberculosis, which is mainly associated with the low-income, poor living conditions, limited access to health care and vulnerability to poor health of this population, and their exclusion from benefits for local residents such as health insurance.
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| 7. |
- Vaezghasemi, Masoud, et al.
(författare)
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The effect of gender and social capital on the dual burden of malnutrition : a multilevel study in indonesia
- 2014
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 9:8, s. e103849-
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Tidskriftsartikel (refereegranskat)abstract
- INTRODUCTION: The paradoxical phenomenon of the coexistence of overweight and underweight individuals in the same household, referred to as the "dual burden of malnutrition", is a growing nutrition dilemma in low- and middle-income countries (LMICs).AIMS: The objectives of this study were (i) to examine the extent of the dual burden of malnutrition across different provinces in Indonesia and (ii) to determine how gender, community social capital, place of residency and other socio-economic factors affect the prevalence of the dual burden of malnutrition.METHODS: The current study utilized data from the fourth wave of the Indonesian Family Life Survey (IFLS) conducted between November 2007 and April 2008. The dataset contains information from 12,048 households and 45,306 individuals of all ages. This study focused on households with individuals over two years old. To account for the multilevel nature of the data, a multilevel multiple logistic regression was conducted.RESULTS: Approximately one-fifth of all households in Indonesia exhibited the dual burden of malnutrition, which was more prevalent among male-headed households, households with a high Socio-economic status (SES), and households in urban areas. Minimal variation in the dual burden of malnutrition was explained by the community level differences (<4%). Living in households with a higher SES resulted in higher odds of the dual burden of malnutrition but not among female-headed households and communities with the highest social capital.CONCLUSION: To improve household health and reduce the inequality across different SES groups, this study emphasizes the inclusion of women's empowerment and community social capital into intervention programs addressing the dual burden of malnutrition.
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