In recent years, Indonesia has experienced rapid increases in severe climate-related disasters have dramatically impacted populations unevenly; the poor and the vulnerable populations are most affected, and adaptive measures are urgently needed to protect and mitigate the impact on their health. However, very little is known about the existing measures addressing climate-related disasters and health impacts among vulnerable groups. WHO established a Health Emergency and Disaster Risk Management framework to urge governments and relevant actors to systematically collect evidence to develop science-based feasible adaptive strategies for priority groups. This study used scoping review methods to identify the action areas of Health-EDRM in policy documents in Indonesia, its content, and any potential gaps that require further study. The results from the documents’ review were then reported and discussed at a national stakeholder consultation meeting. This study has identified several achievements, lessons learned, and challenges from strategies and policies for health adaptation in facing climate-related disasters in Indonesia. This study also proposed strategies and recommendations to support mobilizing and accelerating health adaptation actions towards climate-related disasters in Indonesia.
Climate disasters pose a risk to residents’ well-being globally. However, information about the impact of climate disasters among urban and rural residents remains lacking, especially in Indonesia. This study aims to fill the gap by investigating the impact of climate disaster on subjective well-being based on urban and rural typology model. The data were cross-sectional, involving 7110 Indonesian residents who had experienced climate disasters, 3813 from urban areas and 3297 from rural areas. An ordered probit model was employed to estimate the impact of climate disasters on subjective well-being (i.e., happiness and life satisfaction). In general, the empirical results show that climate disasters do not significantly affect the happiness of Indonesian residents, but they significantly and negatively impact their life satisfaction. Further analysis reveals that climate disasters impact urban and rural residents differently. The subjective well-being of rural residents is more severely affected than those living in urban areas. Further estimation also indicated that climate disaster significantly reduces residents’ subjective well-being at the lowest income level for both rural and urban residents. Our finding confirms that rural residents remain the most vulnerable to the impacts of climate change.
Climate change is almost unanimously perceived to be one of the greatest environmental and developmental challenges of this century. Implementing climate change response requires not just huge and prudent utilization of financial resources, but also highly efficient financing institutions and systems especially in developing countries where underlying development issues such as poverty, health, etc. exist. This paper attempts to evaluate the operationalization of the Indonesian Climate Change Trust Fund (ICCTF) as a climate financing prototype in terms of fund mobilization, nature of projects, equity and inclusion, alignment and mainstreaming. This study was conducted through review of relevant and recent literature on climate change governance and financing, supported with information retrieved from relevant official documents as well as interviews of key persons. Our study found the ICCTF most effective in alignment with national development plans and Sustainable Development Goals (SDGs). It has implemented climate change adaptation programmes with the principles of equity and inclusion of various stakeholders. The ICCTF has however struggled to efficiently mobilize funds owing largely to technical ambiguities especially in its legal and institutional frameworks, it therefore yet to be utilized to its maximum potentials.
BACKGROUND: The intense interactions between people, animals and environmental systems in urban informal settlements compromise human and environmental health. Inadequate water and sanitation services, compounded by exposure to flooding and climate change risks, expose inhabitants to environmental contamination causing poor health and wellbeing and degrading ecosystems. However, the exact nature and full scope of risks and exposure pathways between human health and the environment in informal settlements are uncertain. Existing models are limited to microbiological linkages related to faecal-oral exposures at the individual level, and do not account for a broader range of human-environmental variables and interactions that affect population health and wellbeing. METHODS: We undertook a 12-month health and environmental assessment in 12 flood-prone informal settlements in Makassar, Indonesia. We obtained caregiver-reported health data, anthropometric measurements, stool and blood samples from children < 5 years, and health and wellbeing data for children 5-14 years and adult respondents. We collected environmental data including temperature, mosquito and rat species abundance, and water and sediment samples. Demographic, built environment and household asset data were also collected. We combined our data with existing literature to generate a novel planetary health model of health and environment in informal settlements. RESULTS: Across the 12 settlements, 593 households and 2764 participants were enrolled. Two-thirds (64·1%) of all houses (26·3-82·7% per settlement) had formal land tenure documentation. Cough, fever and diarrhoea in the week prior to the survey were reported among an average of 34.3%, 26.9% and 9.7% of children aged < 5 years, respectively; although proportions varied over time, prevalence among these youngest children was consistently higher than among children 5-14 years or adult respondents. Among children < 5 years, 44·3% experienced stunting, 41·1% underweight, 12.4% wasting, and 26.5% were anaemic. There was self- or carer-reported poor mental health among 16.6% of children aged 5-14 years and 13.9% of adult respondents. Rates of potential risky exposures from swimming in waterways, eating uncooked produce, and eating soil or dirt were high, as were exposures to flooding and livestock. Just over one third of households (35.3%) had access to municipal water, and contamination of well water with E. coli and nitrogen species was common. Most (79·5%) houses had an in-house toilet, but no houses were connected to a piped sewer network or safe, properly constructed septic tank. Median monthly settlement outdoor temperatures ranged from 26·2 °C to 29.3 °C, and were on average, 1·1 °C warmer inside houses than outside. Mosquito density varied over time, with Culex quinquefasciatus accounting for 94·7% of species. Framed by a planetary health lens, our model includes four thematic domains: (1) the physical/built environment; (2) the ecological environment; (3) human health; and (4) socio-economic wellbeing, and is structured at individual, household, settlement, and city/beyond spatial scales. CONCLUSIONS: Our planetary health model includes key risk factors and faecal-oral exposure pathways but extends beyond conventional microbiological faecal-oral enteropathogen exposure pathways to comprehensively account for a wider range of variables affecting health in urban informal settlements. It includes broader ecological interconnections and planetary health-related variables at the household, settlement and city levels. It proposes a composite framework of markers to assess water and sanitation challenges and flood risks in urban informal settlements for optimal design and monitoring of interventions.
In this study, tweets related to fires in Riau, Sumatra, were identified using carefully selected keywords for the 2014-2019 timeframe. The TAGGS algorithm was applied, which allows for geoparsing based on the user’s nationality and hometown and on direct referrals to specific locations such as name of province or name of city in the message itself. Online newspapers covering Riau were analyzed for the year 2019 to provide additional information about the reasons why fires occurred and other factors, such as impact on people’s health, animal mortality related to ecosystem disruption, visibility, decrease in air quality and limitations in the government firefighting response. Correlation analysis between meteorological information, Twitter activity and satellite-derived hotspots was conducted. The existing approaches that BMKG and other Indonesian agencies use to detect fire activity are reviewed and a novel approach for early fire detection is proposed based on the crowdsourcing of tweets. The policy implications of these results suggest that crowdsourced data can be included in the fire management system in Indonesia to support early fire detection and fire disaster mitigation efforts.
There is substantial evidence that in the aftermath of a disaster, an individual’s sense of coherence (SOC) plays an important role in promoting one’s sense of well-being. The SOC is regarded as a core component of the salutogenic model of mental health. Disaster survivors are frequently subjected to traumatic experience and have higher psychological distress prevalence rates than people in the general population. The present study aimed to investigate possible socio-demographic differences (gender and age) on the sense of coherence (SOC) among disaster survivors in Indonesia. A total of 194 respondents (71 male and 123 females) from across the country participated in the online survey. A factorial ANOVA using JASP was conducted to investigate the main effects of gender and age groups and the interaction effect of these variables on the SOC level. The findings were two folds, age group variance was significantly associated with the SOC, while gender did not significantly associate with the SOC. The main effect of Age groups was F (2, 962.773) = 4.307, p = 0.005, indicating a significant difference of SOC between young adult, middle adult, and late adult groups.
Climate-related disasters are increasing across the globe, but their adverse health impacts are unevenly distributed. The people most severely affected tend to be from socio-economically disadvantaged, vulnerable populations, who have high exposure to risk conditions and insufficient adaptive capacity. Despite the increasing health impacts of climate change and disaster risks felt in Asian countries such as China, Indonesia and Vietnam, there are few attempts to access and translate literature and evidence on climate-related disasters and adaptation activities from non-English speaking countries. Conducted by a multi-country project team, this review aims to better understand the current literature and to study gaps in these three countries through an extensive search of literature, in English, Chinese, Indonesian and Vietnamese. Through a systematic review process a total of 298 studies out of 10,139 were included in this study. Key findings confirm that all three countries have experienced increasing climate-related disasters with their associated health impacts, and that adaptation strategies are urgently needed to reduce the risk and vulnerability of the most affected populations. Future studies should consider conducting vulnerability assessments to inform translational research on developing effective adaptation strategies. Authors commented that a common challenge they found was the shortterm nature of disaster response mechanisms, and the lack of long-term investment and policy support for capacity building and multisectoral collaborative research that address the needs of populations vulnerable to climate-related disasters. Thus, to better prepare for future disasters, it is vital that governments and international agencies prioritize funding policies to fill this gap.
Climate change causing an increase of frequency and magnitude of heat waves has a huge impact on the urban population worldwide. In Indonesia, the Southeast Asian country in the tropical climate zone, the increasing heat wave duration due to climate change will be also magnified by projected rapid urbanization. Therefore, not only climate change mitigation measures but also adaptation solutions to more frequent extreme weather events are necessary. Adaptation is essential at local levels. The projected increase of the heat wave duration will trigger greater health-related risks. It will also drive higher energy demands, particularly in urban areas, for cooling. New smart solutions for growing urbanization for reducing urban heat island phenomenon are critical, but in order to identify them, analyzing the changing magnitude and spatial distribution of urban heat is essential. We projected the current and future spatial variability of heat stress index in three cities in Indonesia, namely, Medan, Surabaya, and Denpasar, under climate change and land-cover change scenarios, and quantified it with the Universal Thermal Climate Index (UTCI) for two periods, baseline (1981-2005) and future (2018-2042). Our results demonstrated that currently the higher level of the UTCI was identified in the urban centers of all three cities, indicating the contribution of urban heat island phenomenon to the higher UTCI. Under climate change scenarios, all three cities will experience increase of the heat, whereas applying the land-cover scenario demonstrated that in only Medan and Denpasar, the UTCI is likely to experience a higher increase by 3.1 degrees C; however, in Surabaya, the UTCI will experience 0.84 degrees C decrease in the period 2018-2042 due to urban greening. This study advanced the UTCI methodology by demonstrating its applicability for urban heat warning systems and for monitoring of the urban green cooling effect, as well as it provides a base for adaptation measures’ planning.
As a highly important meteorological hazard, heat waves notably impact human health and socioeconomics, and accurate heat wave risk identification and assessment are effective ways to address this issue. The current spatial scale of heat wave risk assessment is relatively coarse, hardly meeting fine-scale heat wave risk assessment requirements. Therefore, based on multi-source fine-scale remote sensing data and socioeconomic data, this paper evaluates the heat wave risk along the Jakarta-Bandung high-speed railway, obtains the spatial distribution of heat wave risk in 2005, 2014 and 2019, and analyzes spatiotemporal risk variations over the past 15 years. The results show that most high-risk areas were affected by high-temperature hazards. Over time, the hazard, exposure, vulnerability and risk levels increased by 25.82%, 3.31%, 14.82% and 6.97%, respectively, from 2005-2019. Spatially, the higher risk in the northwest is mainly distributed in Jakarta. Additionally, a comparative analysis was conducted on the risk results, and the results showed that the 100-m scale showed more spatial differences than the kilometer scale. The research results in this paper can provide scientific advice on heat wave risk prevention considering the Jakarta-Bandung high-speed railway construction and regional economic and social development.
BACKGROUND: Previous studies focusing on urban, industrialised regions have found that excess heat exposure can increase all-cause mortality, heat-related illnesses, and occupational injuries. However, little research has examined how deforestation and climate change can adversely affect work conditions and population health in low latitude, industrialising countries. METHODS: For this modelling study we used data at 1 km^(2) resolution to compare forest cover and temperature conditions in the Berau regency, Indonesia, between 2002 and 2018. We used spatially explicit satellite, climate model, and population data to estimate the effects of global warming, between 2002 and 2018 and after applying 1·0°C, 1·5°C, and 2·0°C of global warming to 2018 temperatures, on all-cause mortality and unsafe work conditions in the Berau regency, Indonesia. FINDINGS: Between 2002 and 2018, 4375 km(2) of forested land in Berau was cleared, corresponding to approximately 17% of the entire regency. Deforestation increased mean daily maximum temperatures by 0·95°C (95% CI 0·97–0·92; p<0·0001). Mean daily temperatures increased by a population-weighted 0·86°C, accounting for an estimated 7·3–8·5% of all-cause mortality (or 101-118 additional deaths per year) in 2018. Unsafe work time increased by 0·31 h per day (95% CI 0·30–0·32; p<0·0001) in deforested areas compared to 0·03 h per day (0·03–0·04; p<0·0001) in areas that maintained forest cover. With 2·0°C of additional future global warming, relative to 2018, deforested areas could experience an estimated 17-20% increase in all-cause mortality (corresponding to an additional 236-282 deaths per year) and up to 5 h of unsafe work per day. INTERPRETATION: Heat exposure from deforestation and climate change has already started affecting populations in low latitude, industrialising countries, and future global warming indicates substantial health impacts in these regions. Further research should examine how deforestation is currently affecting the health and wellbeing of local communities. FUNDING: University of Washington Population Health Initiative. TRANSLATION: For the Bahasa translation of the abstract see Supplementary Materials section.
In Jambi province, Sumatra, Indonesia, flooding is a recurrent rainy season phenomenon. Historically considered manageable, recent political economic developments have changed this situation. Today, flooding is an environmental hazard and a threat to people’s livelihoods and health. Based on qualitative research and literature that has developed relational approaches to risk and water, we investigate past and present hydrosocial relations in Jambi province and reconstruct the changing meaning of flooding. We suggest that flooding as a hazard in Jambi was produced through the introduction of the plantation industry to the area and its prioritization of dry land for agm-industrial development. This development altered the materiality of water flows, reconfigured power relations and changed the socio-cultural dimensions of flooding. Together, these changes have led to a separation of flooding from its original social and geographic realm, producing new risks and vulnerabilities. This paper provides insights into the material and symbolic dimensions that influence how environmental processes come to be imagined, controlled and contested. It shows how tracing the socionatural production of hazards may help explain the increasingly systemic nature of risks and provide insights into the wider social meaning of environmental risks.
Already climate-related hazards are impacting sanitation systems in Indonesia and elsewhere, and climate models indicate these hazards are likely to increase in frequency and intensity. Without due attention, to maintain existing progress on Sustainable Development Goal 6’s target 6.2 and to increase it to meet ambitions for 2030 will be difficult. City governments need new forms of evidence to respond, as well as approaches to enable them to consider sufficient breadth of strategies to adapt effectively. This paper describes a co-production research process which engaged local governments in four cities in Indonesia experiencing different climate hazards. Local government engagement took place across three stages of (i) inception and design, (ii) participation as key informants and (iii) joint analysis and engagement on the findings. We adapted and simplified a risk prioritisation process based on current literature and employed a novel framework of a ‘climate resilient sanitation system’ to prompt articulation of current and proposed climate change adaptation response actions. In contrast to many current framings of climate resilience in sanitation that focus narrowly on technical responses, the results paint a rich picture of efforts needed by city governments across all domains, including planning, institutions, financing, infrastructure and management options, user awareness, water cycle management and monitoring and evaluation. Local government commitment and improved comprehension on the implications of climate change for sanitation service delivery were key outcomes arising from the co-production process. With strengthened policy and capacity building initiatives from national level, this foundation can be supported, and Indonesian city governments will be equipped to move forward with adaptation actions that protect on-going access to sanitation services, public health and the environment.
The aim of this study was to assess the role of climate variability on the incidence of dengue fever (DF), an endemic arboviral infection existing in Jakarta, Indonesia. The work carried out included analysis of the spatial distribution of confirmed DF cases from January 2007 to December 2018 characterising the sociodemographical and ecological factors in DF high-risk areas. Spearman’s rank correlation was used to examine the relationship between DF incidence and climatic factors. Spatial clustering and hotspots of DF were examined using global Moran’s I statistic and the local indicator for spatial association analysis. Classification and regression tree (CART) analysis was performed to compare and identify demographical and socio-ecological characteristics of the identified hotspots and low-risk clusters. The seasonality of DF incidence was correlated with precipitation (r=0.254, P<0.01), humidity (r=0.340, P<0.01), dipole mode index (r= -0.459, P<0.01) and Tmin (r= -0.181, P<0.05). DF incidence was spatially clustered at the village level (I=0.294, P<0.001) and 22 hotspots were identified with a concentration in the central and eastern parts of Jakarta. CART analysis showed that age and occupation were the most important factors explaining DF clustering. Areaspecific and population-targeted interventions are needed to improve the situation among those living in the identified DF high-risk areas in Jakarta.
Climate is widely known as an important driver to transmit vector-borne diseases (VBD). However, evidence of the role of climate variability on VBD risk in Indonesia has not been adequately understood. We conducted a systematic literature review to collate and critically review studies on the relationship between climate variability and VBD in Indonesia. We searched articles on PubMed, Scopus, and Google Scholar databases that are published until December 2021. Studies that reported the relationship of climate and VBD, such as dengue, chikungunya, Zika, and malaria, were included. For the reporting, we followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. A total of 66 out of 284 studies were reviewed. Fifty-two (78.8%) papers investigated dengue, 13 (19.7%) papers studied malaria, one (1.5%) paper discussed chikungunya, and no (0%) paper reported on Zika. The studies were predominantly conducted in western Indonesian cities. Most studies have examined the short-term effect of climate variability on the incidence of VBD at national, sub-national, and local levels. Rainfall (n = 60/66; 90.9%), mean temperature (T(mean)) (n = 50/66; 75.8%), and relative humidity (RH) (n = 50/66; 75.8%) were the common climatic factors employed in the studies. The effect of climate on the incidence of VBD was heterogenous across locations. Only a few studies have investigated the long-term effects of climate on the distribution and incidence of VBD. The paucity of high-quality epidemiological data and variation in methodology are two major issues that limit the generalizability of evidence. A unified framework is required for future research to assess the impacts of climate on VBD in Indonesia to provide reliable evidence for better policymaking.
This study investigated the contributions of particulate matter (PM) from various emission sources during the dry season, which resulted from frequent fires occurring in degraded forests and peatlands in Indonesia. Samples of fine (PM2.5) and coarse (PM2.5-10) particles collected during the dry season in Riau, Indonesia were analyzed to determine the mass concentrations of metallic trace elements, ionic compound, black carbon (BC), and organic carbon (OC). The average concentrations of PM2.5 and PM2.5-10 at Riau, Indonesia were 63.85 +/- 3.22 mu g m(-3) and 27.72 +/- 2.40 mu g m(-3), respectively. The positive matrix factorization (PMF) model was adopted to identify possible PM sources and their contributions to the ambient PM level. The PMF results identified six major PM2.5 sources, including biomass burning (BB) (28.7%), secondary aerosols (SA) (26.9%), vehicle exhaust (VE) (12.8%), industrial emissions (IE) (12.3%), soil dust (SD) (11.9%), and sea salt (SS) (7.5%). Moreover, there were five primary PM2.5-10 sources, including VE (28.6%) and BB (24%), followed by IE (19.9%), SD (17.2%), and SA (15.3%). A conditional probability function (CPF) analysis revealed that the southeast sector dominated among source direction-dependent contributions. The noncarcinogenic health risks for both adults and children resulting from exposure to PM2.5 were mainly contributed by Co, Ni, and Mn, and carcinogenic risks were caused by the toxic metals Cr and Co. Both noncarcinogenic and carcinogenic health risks resulting from cumulative multielement exposure for both adults and children exceeded acceptable levels. Clearly, more attention should be devoted to reducing the noncarcinogenic and carcinogenic health risks caused by particulate-bound toxic elements through inhalation exposure.
Over the past 30 years, forest fire has been one of main ecological issues in Indonesia. Human-caused deforestation was accused to be the reason behind this matter, apart from the drastic changing in global climate. Palangkaraya is one of the citiesaffected by haze of the forest fire in 2015; considered to be the worst year of forest fire with the value of PM10 was above the normal threshold. As the impact to the community wellbeing, the prevalence of acute respiratory infection (ARI) in October 2015was increasing especially in children. The research aimed to analyse the spatial distribution of children with ARI in October 2015 at Palangkaraya City. Data onARI number were collected from Primary Care under Public Health Office of Palangkaraya City. The PM 10 value was collected bythe Environmental Agency of Palangkaraya City. The spatial analyse method was conducted using theAverage Nearest Neighbour (ANN) method. The result shows that the number of ANN ratio is 0.761801. It means that the distribution pattern of children with ARI in Central Kalimantan during the forest fire in October 2015 was in cluster form.
Smoke from forest fires can reach hazardous levels for extended periods of time. We aimed to determine if there is an association between particulate matter ≤2.5 µm in aerodynamic diameter (PM2.5) and living in a forest fire–prone province and cognitive function. We used data from the Indonesian Family and Life Survey. Cognitive function was assessed by the Ravens Colored Progressive Matrices (RCPM). We used regression models to estimate associations between PM2.5 and living in a forest fire–prone province and cognitive function. In multivariable models, we found very small positive relationships between PM2.5 levels and RCPM scores (PM2.5 level at year of survey: β = 0.1%; 95% confidence interval (CI) [0.01, 0.19%]). There were no differences in RCPM scores for children living in forest fire–prone provinces compared with children living in non-forest fire–prone provinces (mean difference = −1.16%, 95% CI [–2.53, 0.21]). RCPM scores were lower for children who had lived in a forest fire–prone province all their lives compared with children who lived in a non-forest fire–prone province all their life (β = −1.50%; 95% CI [–2.94, –0.07]). Living in a forest fire–prone province for a prolonged period of time negatively affected cognitive scores after adjusting for individual factors.
Children’s bodies are in dynamic stages of development that make them more susceptible to harm from exposure to environmental agents. Children’s physical, physiological and behavioral traits can lead to increased exposure to toxic chemicals or pathogens. In addition, the social determinants of health interact with this exposure and create an increasing risk for further disparities among children. In Indonesia, the fourth most populated country in the world, children are under threat of exposure to contaminated water, air, food and soil, which can cause gastrointestinal and respiratory diseases, birth defects and neurodevelopmental disorders. A safe and balanced nutrition is still an unmet need for too many children. At the same time, the prevalence of obesity and the risk of later development of metabolic diseases, including diabetes and cardiovascular diseases, are increasing as a consequence of both unhealthy diets and inadequate physical activity. The risks of potential long-term toxicity, including carcinogenic, neurotoxic, immunotoxic, genotoxic, endocrine-disrupting and allergenic effects of many chemicals, are also close to their lives. This paper provides an overview of common disease risks in Indonesian children, including: acute hepatitis A, diarrheal diseases, dengue and malaria due to lack of water supply and sanitation, vectors, and parasites; asthma, bronchopneumonia, chronic obstructive pulmonary disease (COPD) and acute respiratory infections (ARIs) due to air pollution and climate change; some chronic diseases caused by toxic and hazardous waste; and direct or indirect consequences due to the occurrence of disasters and health emergencies.
Medical statistics collected by WHO indicates that dengue fever is still ravaging developing regions with climates befitting mosquito breeding amidst moderate-to-weak health systems. This work initiates a study over 2009-2017 panel data of dengue incidences and meteorological factors in Jakarta, Indonesia to bear particular understanding. Using a panel random-effect model joined by the pooled estimator, we show positively significant relationships between the incidence level and meteorological factors. We ideate a clustering strategy to decompose the meteorological datasets into several more datasets such that more explanatory variables are present and the zero-inflated problem from the incidence data can be handled properly. The resulting new model gives good agreement with the incidence data accompanied by a high coefficient of determination and normal zero-mean error in the prediction window. A risk measure is characterized from a one-step vector autoregression model relying solely on the incidence data and a threshold incidence level separating the low-risk and high-risk regime. Its magnitude greater than unity and the weak stochastic convergence to the endemic equilibrium mark a persistent cyclicality of the disease in all the five districts in Jakarta. Moreover, all districts are shown to co-vary profoundly positively in terms of epidemics occurrence, both generally and timely. We also show that the peak of incidences propagates almost periodically every year on the districts with the most to the least recurrence: Central, South, West, East, and North Jakarta.
BACKGROUND: Dengue is one of the most rapidly spreading vector-borne diseases, which is considered to be a major health concern in tropical and sub-tropical countries. It is strongly believed that the spread and abundance of vectors are related to climate. Construction of climate-based mathematical model that integrates meteorological factors into disease infection model becomes compelling challenge since the climate is positively associated with both incidence and vector existence. METHODS: A host-vector model is constructed to simulate the dynamic of transmission. The infection rate parameter is replaced with the time-dependent coefficient obtained by optimization to approximate the daily dengue data. Further, the optimized infection rate is denoted as a function of climate variables using the Autoregressive Distributed Lag (ARDL) model. RESULTS: The infection parameter can be extended when updated daily climates are known, and it can be useful to forecast dengue incidence. This approach provides proper prediction, even when tested in increasing or decreasing prediction windows. In addition, associations between climate and dengue are presented as a reversed slide-shaped curve for dengue-humidity and a reversed U-shaped curves for dengue-temperature and dengue-precipitation. The range of optimal temperature for infection is 24.3-30.5 °C. Humidity and precipitation are positively associated with dengue upper the threshold 70% at lag 38 days and below 50 mm at lag 50 days, respectively. CONCLUSION: Identification of association between climate and dengue is potentially useful to counter the high risk of dengue and strengthen the public health system and reduce the increase of the dengue burden.
OBJECTIVE: The aim of this study was to screening PTSD among flood victims in Indonesia. METHOD: Quantitative non-experimental research method with a descriptive cross-sectional study. There were 356 flooding victims who participated in this study using purposive sampling techniques. The questionnaire used was PCL 5 DSM-V to determine the incidence of PTSD. RESULTS: The results of the study reported that 52% experiencing PTSD, and 48% did not experience PTSD. The majority of symptoms of PTSD were re-experiencing (98.3%). CONCLUSIONS: It can be concluded that the incidence of PTSD could arise at any age, gender, level of education and occupation by experiencing symptoms of re-experiencing, avoidance, negative alteration in mood cognition and hyperarousal. Hence, this study suggested improving intervention to decrease symptoms of PTSD.
Because of fast-paced industrialization, urbanization, and population growth in Indonesia, there are serious health issues in the country resulting from air pollution. This study uses geospatial modelling technologies, namely land-use regression (LUR), geographically weighted regression (GWR), and geographic and temporal weighted regression (GTWR) models, to assess variations in particulate matter (PM(10)) and nitrogen dioxide (NO(2)) concentrations in Surabaya City, Indonesia. This is the first study to implement spatiotemporal variability of air pollution concentrations in Surabaya City, Indonesia. To develop the prediction models, air pollution data collected from seven monitoring stations from 2010 to 2018 were used as dependent variables, while land-use/land cover allocations within a 250 m to 5000 m circular buffer range surrounding the monitoring stations were collected as independent variables. A supervised stepwise variable selection procedure was applied to identify the important predictor variables for developing the LUR, GWR, and GTWR models. The developed models of LUR, GWR, and GTWR accounted for 49%, 50%, and 51% of PM(10) variations and 46%, 47%, and 48% of NO(2) variations, respectively. The GTWR model performed better (R(2) = 0.51 for PM(10) and 0.48 for NO(2)) than the other two models (R(2) = 0.49-0.50 for PM(10) and 0.46-0.47 for NO(2)), LUR and GWR. In the PM(10) model four predictor variables, public facility, industry and warehousing, paddy field, and normalized difference vegetation index (NDVI), were selected during the variable selection procedure. Meanwhile, paddy field, residential area, rainfall, and temperature played important roles in explaining NO(2) variations. Because of biomass burning issues in South Asia, the paddy field, which has a positive correlation with PM(10) and NO(2), was selected as a predictor. By using long-term monitoring data to establish prediction models, this model may better depict PM(10) and NO(2) concentration variations within areas across Asia.
