Risk-prone Areas Research Articles

Probability Scale of Vessel Risks on a Shipping Company

Indonesia as one of the biggest maritime country in the world, makes sea transportation an important mode of transportation in Indonesia. A sea transportation is a vessel owned by a shipowner or shipping company. The owners have responsibilities in the operation of vessels and its cargos. Shipowners barely understand the risks that follow them on the sailing such as PT X. This private company is one of shipping companies that has sailing route from Surabaya to west Indonesia. High level of vessel accidents in west Indonesia makes the Java Sea a risk-prone area by NTSC. This paper reports interview with PT X and validated by a marine expert to analyze risk factors in vessels. The method conducted was a survey to collect mean index data for probability risk analysis. It is identified that the highest probability of risk is caused by the lack of experiences from the crews, work accidents on the boat, high fuel cost and others. Hence, this report concludes that this examination of risk probability of ship events to a ship company shows types of risk that have the highest probability in order to be mitigated so that the loss will be able to be reduced

Place attachment in natural hazard-prone areas and decision to relocate: Research review and agenda for developing countries

There is a growing interest in understanding the effects of place attachment as a coping strategy in response to natural hazard risk. Place attachment is based on the domain of interpersonal relationships and can be a potential parameter to influence an individual's risk perception and coping strategies in areas facing natural hazard. The aim of this systematic literature review is to assess the current state of research linking place attachment to voluntary migration among residents living in natural hazard prone areas in developing countries. While place attachment has several collective benefits and improves one's quality of life, it can be dysfunctional by reducing the perceived risk of hazard. Place attachment provides a sense of security to the residents and contributes to one's self-identity. The review finds that residents who are strongly attached to their place are unlikely to leave even when the risk is high. This is especially the case where the place attachment is related to religious beliefs and where the social capital is high. The review also identified that place attachment helped communities to better prepare for natural hazard in the pre-disaster period. The review calls for further research to unravel the complexity between place attachment and voluntary migration from natural hazard risk-prone areas.

Spatial risk assessment of an emerging pandemic under data scarcity: A case of COVID-19 in Eswatini

Coronavirus (COVID-19) has rapidly spread across many countries in pandemic proportions since the first case was reported in Hubei, China in December 2019. Understanding transmission, susceptibility and exposure risks is crucial for surveillance, control and response to the disease. Knowing the geographic distribution of health resource scarcity areas is necessary if a country is to adequately anticipate and prepare for the full impact of infections. We explored the potential to undertake a spatial risk assessment of an emerging pandemic under data scarcity in Eswatini. We used a set of socio-economic and demographic variables to identify epidemic risk prone areas in the country. Three risk zone levels for COVID-19 were identified in the country. The analysis showed that about 29% (320 818) of the population were located in the high risk zone and these were people who could potentially be infected with COVID-19 in the absence of mitigation measures. A majority of cases and deaths attributed to COVID-19 would likely remain unknown but our estimate could be used to gauge the full burden of the disease. Approximating and quantifying the number of people who may be potentially infected with COVID-19 remains impossible under data scarcity and limited healthcare capacity especially in sub-Saharan Africa. We provided an estimation method that could support the pandemic risk forecasting, preparedness and response measures in the midst of data scarcity. The resultant map products could be used to guide on-the-ground surveillance and response efforts.

Analysing vulnerability of road network and guiding evacuees to sheltered areas: Case study of Mt Merapi, Central Java, Indonesia

Historically people traded the risk of living in dangerous places such as volcanic slopes for the benefit of farming in rich soils. Road network around risk prone area plays a key role in saving lives when evacuation is required in an emergency, and thus needs to be in full preparedness to face the eventuality. This will need analysing vulnerability to disruption and identifying critical network links of the evacuation routes. It is also crucial to ensure that the evacuees are aware of recommended routes to sheltered areas. Traffic models to assess road network performance due to natural disasters have been developed in the past. But few researchers investigated whether the evacuees are aware of the recommended routes to sheltered areas and whether they are willing to use them indeed. This paper adopts a vulnerability index and identifies network links to improve, by mapping them to a simple ‘traffic light style’ congestion scale. A special mobile phone application software was developed to guide the residents to reach sheltered areas which takes account of the fact that a third of the residents living around Mt Merapi are not aware of evacuation routes to sheltered areas.

Atmospheric Volatile Organic Compounds (VOCs) in China: a Review

The purpose of this review is to summarize the current understandings of atmospheric VOC characteristics in China and put forward the methodological drawbacks of the VOC measurement that need to be resolved and the research gaps that need to be filled. Whereas in recent investigations in the North China Plain (NCP) a reduction (20–66%) in total VOC concentration is noticed compared with the ones published before 2015, an increase (13–127%) is observed for the Yangtze River Delta (YRD) region. Aromatics and oxygenated VOCs are frequently appearing as the most abundant VOC group in recent investigations. Industry-related VOC sources are more dominant in the YRD regions while vehicle-related sources are more influential in the NCP, Central China, and Pearl River Delta regions. Benzene, 1,3,5-trimethylbenzene, ethylbenzene, naphthalene, dichloromethane, 1,2-dichloroethane, 1,2-dichloropropane, chloroform, carbon tetrachloride, and 1,2-dibromoethane pose carcinogenic risk to exposed population in China and the most risk-prone areas are affected by the petrochemical industry, biomass burning, waste management, and vehicle emissions. Formaldehyde and toluene have relatively high concentrations among the different indoor VOCs observed and their concentrations noticed to be exceeded the national air quality standard. More investigations have to be performed on rarely studied health risk assessment of VOCs and characterization of indoor VOCs. BVOC studies are rarely conducted in China, which has to be performed on common plant species, different forest, and agricultural crops. VOC characterization in forest fire smokes and more process-specific emission characteristics in common industries need to be conducted.

Risk Mapping for the Sustainable Protection of Cultural Heritage in Extreme Changing Environments

Cultural heritage is widely recognized to be at risk due to the impact of climate change and associated hazards, such as events of heavy rain, flooding, and drought. User-driven solutions are urgently required for sustainable management and protection of monumental complexes and related collections exposed to changes of extreme climate. With this purpose, maps of risk-prone areas in Europe and in the Mediterranean Basin have been produced by an accurate selection and analysis of climate variables (daily minimum and maximum temperature—Tn and Tx, daily cumulated precipitation—RR) and climate-extreme indices (R20mm, R95pTOT, Rx5 day, CCD, Tx90p) defined by Expert Team on Climate Change Detection Indices (ETCCDI). Maps are available to users via an interactive Web GIS (Geographic Information System) tool, which provides evaluations based on historical observations (high-resolution gridded data set of daily climate over Europe—E-OBS, 25 km) and climate projections (regional climate models—RCM, ~12 km) for the near and far future, under Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios. The tool aims to support public authorities and private organizations in the decision making process to safeguard at-risk cultural heritage. In this paper, maps of risk-prone areas of heavy rain in Central Europe (by using R20mm index) are presented and discussed as example of the outputs achievable by using the Web GIS tool. The results show that major future variations are always foreseen for the 30-year period 2071–2100 under the pessimistic scenario (RCP 8.5). In general, the coastal area of the Adriatic Sea, the Northern Italy, and the Alps are foreseen to experience the highest variations in Central Europe.

CovidSens: a vision on reliable social sensing for COVID-19

With the spiraling pandemic of the Coronavirus Disease 2019 (COVID-19), it has becoming inherently important to disseminate accurate and timely information about the disease. Due to the ubiquity of Internet connectivity and smart devices, social sensing is emerging as a dynamic AI-driven sensing paradigm to extract real-time observations from online users. In this paper, we propose CovidSens, a vision of social sensing-based risk alert systems to spontaneously obtain and analyze social data to infer the state of the COVID-19 propagation. CovidSens can actively help to keep the general public informed about the COVID-19 spread and identify risk-prone areas by inferring future propagation patterns. The CovidSens concept is motivated by three observations: (1) people have been actively sharing their state of health and experience of the COVID-19 via online social media, (2) official warning channels and news agencies are relatively slower than people reporting their observations and experiences about COVID-19 on social media, and (3) online users are frequently equipped with substantially capable mobile devices that are able to perform non-trivial on-device computation for data processing and analytics. We envision an unprecedented opportunity to leverage the posts generated by the ordinary people to build a real-time sensing and analytic system for gathering and circulating vital information of the COVID-19 propagation. Specifically, the vision of CovidSens attempts to answer the questions: How to distill reliable information about the COVID-19 with the coexistence of prevailing rumors and misinformation in the social media? How to inform the general public about the latest state of the spread timely and effectively, and alert them to remain prepared? How to leverage the computational power on the edge devices (e.g., smartphones, IoT devices, UAVs) to construct fully integrated edge-based social sensing platforms for rapid detection of the COVID-19 spread? In this vision paper, we discuss the roles of CovidSens and identify the potential challenges in developing reliable social sensing-based risk alert systems. We envision that approaches originating from multiple disciplines (e.g., AI, estimation theory, machine learning, constrained optimization) can be effective in addressing the challenges. Finally, we outline a few research directions for future work in CovidSens.

Geovisualization and Geographical Analysis for Fire Prevention

Swedish emergency services still have relatively limited resources and time for proactive fire prevention. As a result of this, there is an extensive need for strategic working methods and knowledge to take advantage of spatial analyses. In addition, decision-making based on visualizations and analyses of their own collected data has the potential to increase the validity of strategic decisions. The objective of this paper is to critically examine how some different geovisualization techniques—point data, kernel density and choropleth mapping—actively can complement each other and be applied in fire preventive work. The results show that each technique itself has limitations, but that, in combination, they increase the scope for interpretation and the possibilities of targeting different forms of preventive measures. The investigated geovisualization techniques facilitate various forms of fire prevention such as identifying which areas to prioritize for outreach, home visits, identification and targeting of different risk groups and customized information campaigns about certain types of fires in risk-prone areas. Furthermore, fairly simple mapping techniques can be utilized directly to evaluate incident reports and increase the quality of geocoded fire incidents. The study also shows how some of these techniques can be applied when analyzing residential fire incidents and their relation to underlying structural and socio-economic factors as well as spatio-temporal dimensions of fire incident data. The spatial analyses and supporting maps can help find and predict risk areas for residential fires or be used directly to formulate hypotheses on fire patterns. The generic functionality of the visualization methods makes them also useful for visual analysis of other types of incidents, such as reported crimes and accidents. Finally, the results are applicable to a work process adapted to the Swedish legislation on confidential data.

Perceived Arrival Time of Disaster Relief Supplies Matters for Household Preparedness for Natural Disasters

This paper addresses whether and to what extent individual subjective perception of the time it takes for disaster relief supplies to arrive (i.e., perceived arrival time) affects households’ emergency drinking water (EDW) preparedness behavior for natural disasters, based on household data originally collected through an internet survey in Japan in 2013. Our estimation results show that perceived arrival time significantly matters for household stocks of EDW and that the amount of EDW could be greatly enhanced as perceived arrival time increases. Moreover, households in risk-prone areas stock more EDW compared with households in less risk-prone areas. Perceived arrival time can be interpreted as a kind of risk perception, and our results illustrate the counterexample of the so-called risk perception paradox.

Demand for Complementary Financial and Technological Tools for Managing Drought Risk

Innovations that mitigate weather-related production risks can potentially benefit farmers in risk-prone areas. We examine two distinct tools for managing drought risk: (1) weather index insurance and (2) a drought-tolerant (DT) rice variety. Although these tools can independently address drought risk, we demonstrate the additional benefits gained by bundling them into a complementary product. Results suggest that farmers are generally unwilling to adopt the DT variety independent of insurance, largely due to a yield penalty under nondrought conditions. When bundled with insurance, however, farmers’ valuation of the variety increases. Farmers value insurance on its own but even more so when it is bundled with the DT variety. We provide evidence that farmers value the complementarities inherent in a well-calibrated bundle of risk management tools.

Major environmental and socioeconomic determinants of cutaneous leishmaniasis in Brazil - a systematic literature review.

Cutaneous leishmaniasis (CL) is a zoonotic disease with complex transmission cycle. Some environmental and socioeconomic factors are known to be the major determinants of the transmission process, which are involved in configuring the spatiotemporal patterns and thus can be delimiting. However, the relevance of these socioeconomic and environmental determinants is still not well understood. In this study, we aimed to identify the major environmental and socioeconomic determinants of CL in Brazil by articulating a systematic literature review of studies that are based on this subject. The methodology included a search for studies according to a structured protocol using the scientific platforms, such as Scielo and PubMed. The references of each identified article were who referred to CL determinants were further screened, and so on. We extracted information from 41 articles and the determinants were grouped accordingly. Two measures were evaluated as follows: a) the frequency of citations of the determinants; and b) the proportion of determinants identified as having "significant association in analytical studies" with respect to the total number of determinants analyzed in other analytical studies using the same concept. The analyzed articles covered most of the regions of Brazil and 7 other countries bordering Brazil. We found 43 concepts of determinants. However, the final selection resulted in the identification of 14 major determinants. These results therefore contribute in the identification of major CL determinants and this information can be used to establish strategies for identifying risk prone areas for disease surveillance.

The spatial and temporal distribution, species composition, and host preference of phlebotomine sand flies in the Bethlehem District of Palestine

In the Palestinian West Bank, leishmaniasis is emerging as a serious public health issue with incidence increasing over time, especially in the western and the northern parts. This study was aimed to evaluating the effect of altitude on sand fly density, temporal and spatial distribution, species composition, and host preference within and between three villages in the Bethlehem District. The three villages occur along an elevation cline, ranging from the disease-free area of Kisan (KIS; 732–782 m ASL), down to the endemic areas of Arab Ar-Rashaiyda (AAR; 522–568 m ASL), and Al‘Azazma (AZA; 473–510 m ASL) in the Bethlehem District (southeastern West Bank). Sand flies were trapped monthly from May through October in 2013 in traps located north, south, east, and west of each village. The abundance of sand flies differed among the three villages, with Arab Ar-Rashaiyda (AAR) > Al ‘Azazma (AZA) >Kisan (KIS). The sex ratio was even in AAR and AZA, and female biased in KIS. Both male and female Phlebotomus sand fly densities varied with elevation, with greatest densities found at intermediate elevations (AAR). Elevation correlated negatively with the proportion of blood-fed Phlebotomus females. Male Phlebotomus species composition differed among sites, with all the species found in this study present in AZA, while some species were absent from AAR and KIS. The host blood species engorged by P. sergenti were grouped in four categories: human (45.5%), livestock (25%), avian (19.9%), and dog (9.6%). This study provided information about the spatial and temporal distribution, age and species composition, and host preference of sand fly vectors that influence disease transmission. This information will allow us to better target sand flies, to control the disease, and to monitor risk prone areas.

Modelagem 3D e geovisualização aplicada a desastres naturais. Uma proposta de laboratório de ensino e pesquisa para monitoramento e previsão de escorregamentos

Landslides have a high degree of uncertainty requiring new methods for their analysis, monitoring and forecasting. In Brazil, Cemaden is responsible for actions related to the natural disasters and, recently, has started with partner institutions, a project sponsored by FINEP in order to monitor ten prone-landslides areas situated in different regions of the country. This paper presents the proposal of REDEGEO to implant a laboratory of modeling and geovisualization to study landslide processes in urbanized areas. The laboratory consists of three parts: A) Field surveys to obtain high resolution images from unmanned aerial vehicles and to obtain the internal geometry of outcrops from geophysics methods (Resistivity and Radar Soil Penetration - GPR); B) 3D modeling using the software Geovisionary® which allows the analysis of image and geophysical dataset from different formats considering their volumetric properties; C) Geovisualization and Virtual Reality (VR) where the images obtained in the fieldwork can be observed from a human-machine interface which allows that the researchers have a full immersion in the selected areas. The creation of a laboratory related to the natural disasters, which include geovisualization and VR, stimulates the active participation of the researcher team and creates mechanisms for the participation of technologies developers, managers, civil defense agents and even the population that lives in the risk prone-areas.

A deterministic and stochastic assessment for exposure and risk of arsenic via ingestion of edible crops.

Natural arsenic contamination is a critical problem for various places around the world. Simav Plain (Kutahya, Turkey) is one such area that was shown to have natural arsenic contamination in its waters and soils. Arsenic exposure through ingestion of edible crops cultivated in Simav Plain and associated health risks were assessed in this study. To achieve this objective, arsenic levels in 18 crop species were estimated based on measured soil arsenic concentrations. Individual and aggregate non-carcinogenic and carcinogenic risks associated with ingestion of arsenic-contaminated crops were then assessed with scenario-based deterministic point estimates and stochastic population estimates. Monte Carlo simulation was used for the estimation of population health risks. Accordingly, wheat was found as the highest-ranked crop specie for the both types of health risks, followed by tomato and potato, which are three of the most consumed crops in the region. The risk levels estimated in this study were relatively high, indicating consumption of crops grown in the plain may be posing significant health risks even at lower-bound estimates. Consuming wheat, tomato, potato, and their products from uncontaminated sources was found to reduce the aggregate risks up to 88% implicating the importance of proposing suitable management measures for similar risk-prone areas.

Radon and Thoron; Radioactive Gases Lurking in Earthen Houses in Rural Kenya.

In this paper, documented studies on radon and thoron concentrations in earthen dwellings and 238U and 232Th concentrations in soil in Kenya are reviewed. High concentrations of the isotopes were recorded in the earthen dwellings despite being generally well ventilated. Mrima Hill in the Coast region recorded the highest thoron levels with a mean of 652 Bq m−3. Twenty five percent of dwellings had thoron concentration in excess of 1,000 Bq m−3. Notably high indoor radon levels were recorded in Taita Taveta also in the Coast region, and in Kenyatta University situated in Nairobi in the Central region of the country. Radon concentration in the Rift Valley region was found to be too low to contribute significantly to radiation exposure. Based on studies on the concentration of 238U and 232Th in soil, the Southwestern region of the country was anticipated to have elevated radon/thoron concentrations in earthen dwellings. Existing studies involving measurement of indoor radon and thoron, and 226Ra and 232Th in soil are relatively few and of a small scale. More extensive studies are therefore necessary not only to corroborate the risk projections but to also generate sufficient data to enable countrywide mapping of indoor radon/thoron risk-prone areas.

Spatial targeting of ICT-based weather and agro-advisory services for climate risk management in agriculture

The increasing frequency of climatic risks, such as flood, drought, heat and cold waves, is causing significant loss of farm productivity and income in agriculturally dependent communities. Timely availability of reliable information on weather conditions, agro-advisories, and market information can help to minimize losses in agriculture. This paper presents a scientific and integrated approach to identify areas of high agriculture vulnerability to climate change and availability of ICT services for dissemination of CSA information in the vulnerable areas. This study was illustrated for India where the majority of the population depends on agriculture for their livelihoods, and this sector is highly vulnerable to climate change. The study presents four regions: i) high agriculture vulnerability and low ICT services, ii) high agriculture vulnerability and high ICT services, iii) low agriculture vulnerability and low ICT services, and iv) low agriculture vulnerability and high ICT services. This methodology, which is simple, uses available data, and is easy to apply, can be useful to prioritize locations for climate-smart interventions, mode of CSA information dissemination using ICT services, and increase coverage of agro-ICT services through development of ICT services in the locations where climate change impact is high and ICT services are very low. This study also showed that there is a need to improve the quality of existing climate information and agro-advisory services in the climate risk-prone areas.

Geostatistical modeling of dengue disease in Lahore, Pakistan

Dengue outbreak has become a significant mosquito-borne disease in Pakistan with the worst outbreak in the Lahore district in 2011. This situation has emerged as a serious concern for disaster management authorities, and managing risks of dengue outbreaks has become their top priority. This study investigated the relationship of the reported dengue cases in the Lahore district in 2011 with the spatial and temporal changes in climatic and environmental factors. The quantitative co-relational research method was employed to ascertain the association between dengue incidences and weather parameters, land use/cover, and demographic characteristics of the study area. Ordinary least-square and geographically weighted regression analyses were conducted to identify the influence of study variables on the dengue outbreak. Satellite and ground data were used to derive study parameters. A geostatistical dengue risk model was developed to identify the risk-prone areas in Lahore. The geographically weighted multivariate regression model indicated a statistically significant relationship between dengue cases and the built-up area and population density. These two explanatory variables explained 77.4% variance in dengue incidences. This study supported the association between the demographic parameters and distribution pattern of dengue outbreaks in the Lahore district. The dengue risk model identified the vulnerable areas that need particular attention to mitigate future outbreaks.

Sentinel-1 InSAR Coherence to Detect Floodwater in Urban Areas: Houston and Hurricane Harvey as A Test Case

This paper presents an automatic algorithm for mapping floods. Its main characteristic is that it can detect not only inundated bare soils, but also floodwater in urban areas. The synthetic aperture radar (SAR) observations of the flood that hit the city of Houston (Texas) following the landfall of Hurricane Harvey in 2017 are used to apply and validate the algorithm. The latter consists of a two-step approach that first uses the SAR data to identify buildings and then takes advantage of the Interferometric SAR coherence feature to detect the presence of floodwater in urbanized areas. The preliminary detection of buildings is a pre-requisite for focusing the analysis on the most risk-prone areas. Data provided by the Sentinel-1 mission acquired in both Strip Map and Interferometric Wide Swath modes were used, with a geometric resolution of 5 m and 20 m, respectively. Furthermore, the coherence-based algorithm takes full advantage of the Sentinel-1 mission’s six-day repeat cycle, thereby providing an unprecedented possibility to develop an automatic, high-frequency algorithm for detecting floodwater in urban areas. The results for the Houston case study have been qualitatively evaluated through very-high-resolution optical images acquired almost simultaneously with SAR, crowdsourcing points derived by photointerpretation from Digital Globe and Federal Emergency Management Agency’s (FEMA) inundation model over the area. For the first time the comparison with independent data shows that the proposed approach can map flooded urban areas with high accuracy using SAR data from the Sentinel-1 satellite mission.

A GIS-Based Artificial Neural Network Model for Spatial Distribution of Tuberculosis across the Continental United States.

Despite the usefulness of artificial neural networks (ANNs) in the study of various complex problems, ANNs have not been applied for modeling the geographic distribution of tuberculosis (TB) in the US. Likewise, ecological level researches on TB incidence rate at the national level are inadequate for epidemiologic inferences. We collected 278 exploratory variables including environmental and a broad range of socio-economic features for modeling the disease across the continental US. The spatial pattern of the disease distribution was statistically evaluated using the global Moran’s I, Getis–Ord General G, and local Gi* statistics. Next, we investigated the applicability of multilayer perceptron (MLP) ANN for predicting the disease incidence. To avoid overfitting, L1 regularization was used before developing the models. Predictive performance of the MLP was compared with linear regression for test dataset using root mean square error, mean absolute error, and correlations between model output and ground truth. Results of clustering analysis showed that there is a significant spatial clustering of smoothed TB incidence rate (p < 0.05) and the hotspots were mainly located in the southern and southeastern parts of the country. Among the developed models, single hidden layer MLP had the best test accuracy. Sensitivity analysis of the MLP model showed that immigrant population (proportion), underserved segments of the population, and minimum temperature were among the factors with the strongest contributions. The findings of this study can provide useful insight to health authorities on prioritizing resource allocation to risk-prone areas.

Prevalence and knowledge of scrub typhus in patients with acute febrile illness in teaching hospital, Chitwan, Nepal

Background: Infection from scrub typhus has been documented in different areas of Nepal and Chitwan is one of the risk-prone areas. Objective: This study aimed to find out the prevalence of scrub typhus in patients suffering from an acute febrile illness (AFI) as well as their knowledge about it. Materials and Methods: Descriptive study was conducted in Chitwan Medical College (CMC), a tertiary care teaching hospital in Chitwan. A total of 301 patients with AFI admitted in different medical units and screened for scrub typhus by immunoglobulin M enzyme-linked immunosorbent assay method were selected purposively as a study sample. Face to face interview, record review, and blood reports were used to collect the required information. Data were collected from May 1, 2018, to December 2018. Before data collection, ethical approval was obtained from CMC Institutional Review Committee. Obtained data were entered into IBM-SPSS version 20 for window and analyzed using descriptive and inferential statistics. Results: The findings of the study revealed that 13.3% of patients with AFI were positive for scrub typhus. The most common symptoms among patients were fever (100%), headache (59.1%), vomiting (27.0%), and cough (26.7%). Out of 301 patients, only 70 (23.3%) had heard about scrub typhus. Among 70 patients, more than half 41 (58.6%) had a high level of knowledge on scrub typhus. On item wise knowledge, more than half of the patients knew that scrub typhus as infectious disease (52.9%), transmitted through the bite of mites (61.4%) but not transmitted through person to person (65.7%). However, only 38.6% knew that scrub typhus rapidly spread in the rainy season. Moreover, less than half of the patients knew that wearing closed footwear (41.4%), using insect repellents (48.6%), and avoiding traveling to mite infected areas (45.7%) are the preventive measures of scrub typhus. Conclusion: Our results highlight that scrub typhus infection is an important cause of AFI, and patients must be routinely screened for the proper diagnosis and timely treatment. Moreover, very few had heard about scrub typhus and its preventive measures, so awareness program on scrub typhus is needed for the risk groups to enhance their knowledge.