Population Density Patterns Research Articles

Understanding contributors to racial and ethnic inequities in COVID-19 incidence and mortality rates.

Racial inequities in Coronavirus 2019 (COVID-19) have been reported over the course of the pandemic, with Black, Hispanic/Latinx, and Native American individuals suffering higher case rates and more fatalities than their White counterparts. We used a unique statewide dataset of confirmed COVID-19 cases across Missouri, linked with historical statewide hospital data. We examined differences by race and ethnicity in raw population-based case and mortality rates. We used patient-level regression analyses to calculate the odds of mortality based on race and ethnicity, controlling for comorbidities and other risk factors. As of September 10, 2020 there were 73,635 confirmed COVID-19 cases in the State of Missouri. Among the 64,526 case records (87.7% of all cases) that merged with prior demographic and health care utilization data, 12,946 (20.1%) were Non-Hispanic (NH) Black, 44,550 (69.0%) were NH White, 3,822 (5.9%) were NH Other/Unknown race, and 3,208 (5.0%) were Hispanic. Raw cumulative case rates for NH Black individuals were 1,713 per 100,000 population, compared with 2,095 for NH Other/Unknown, 903 for NH White, and 1,218 for Hispanic. Cumulative COVID-19-related death rates for NH Black individuals were 58.3 per 100,000 population, compared with 38.9 for NH Other/Unknown, 19.4 for NH White, and 14.8 for Hispanic. In a model that included insurance source, history of a social determinant billing code in the patient's claims, census block travel change, population density, Area Deprivation Index, and clinical comorbidities, NH Black race (OR 1.75, 1.51-2.04, p<0.001) and NH Other/Unknown race (OR 1.83, 1.36-2.46, p<0.001) remained strongly associated with mortality. In Missouri, COVID-19 case rates and mortality rates were markedly higher among NH Black and NH Other/Unknown race than among NH White residents, even after accounting for social and clinical risk, population density, and travel patterns during COVID-19.

Population density, habitat use and activity patterns of endangered hog deer in Cambodia

Population density, habitat use and activity patterns of endangered hog deer in Cambodia

Applying the workload indicators of staffing needs method in nursing health workforce planning: evidences from four hospitals in Vietnam

BackgroundVietnam has encountered difficulties in ensuring an adequate and equitable distribution of health workforce. The traditional staffing norms stated in the Circular 08/TT-BYT issued in 2007 based solely on population or institutional size and do not adequately take into consideration the variations of need such as population density, mortality and morbidity patterns. To address this problem, more rigorous approaches are needed to determine the number of personnel in health facilities. One such approach is Workload Indicators of Staffing Need (WISN) developed by the World Health Organization (WHO), a facility-based workforce planning method that assists managers in defining the responsibilities of different workforce categories and improving the appropriateness and efficiency of a staff mix.MethodsThis study applied the WISN approach and was employed in 22 clinical departments at four hospitals in Vietnam between 2015 and 2018. 22 targeted group discussions involving nurses were conducted. Hospital personnel records have been retrieved. The data were analyzed according to WISN instructions.ResultsOf the 22 departments, there was a shortage of 1 to 2 nurses in 10 departments, with WISN ratios ranging between 0.88 and 0.95. Only 01 clinical colleges at Can Tho Hospital lacked 05 nurses, facing a high workload with a WISN ratio of 0.78. Administrative time represented 20–40% of the total work time of a nurse. In comparison, nurses at Can Tho Hospital spent time on administration from 24 onwards. 5–41.7% of their working time while nurses at Thanh Hoa Hospital spent 21–33%.ConclusionsThe application of the WISN enabled health managers to analyze the workload of nurses, calculate staffing needs, and thus effectively contribute to the workforce planning process. It is expected that the results of this research will encourage the use of the WISN tool in other hospitals and health facilities across the health system. At provincial and national levels, this study provides important evidence to help policy makers develop guidelines for personnel norms for health facilities in the context of limited resources, while the existing regulation is no longer appropriate.

Population density and activity patterns of the leopard cat (&lt;i&gt;Prionailurus bengalensis&lt;/i&gt;) in southern China: Estimates based on camera-trapping data

Population density and activity patterns of the leopard cat (&lt;i&gt;Prionailurus bengalensis&lt;/i&gt;) in southern China: Estimates based on camera-trapping data

The effect of landscape fragmentation on Turing-pattern formation.

Diffusion-driven instability and Turing pattern formation are a well-known mechanism by which the local interaction of species, combined with random spatial movement, can generate stable patterns of population densities in the absence of spatial heterogeneity of the underlying medium. Some examples of such patterns exist in ecological interactions between predator and prey, but the conditions required for these patterns are not easily satisfied in ecological systems. At the same time, most ecological systems exist in heterogeneous landscapes, and landscape heterogeneity can affect species interactions and individual movement behavior. In this work, we explore whether and how landscape heterogeneity might facilitate Turing pattern formation in predator-prey interactions. We formulate reaction-diffusion equations for two interacting species on an infinite patchy landscape, consisting of two types of periodically alternating patches. Population dynamics and movement behavior differ between patch types, and individuals may have a preference for one of the two habitat types. We apply homogenization theory to derive an appropriately averaged model, to which we apply stability analysis for Turing patterns. We then study three scenarios in detail and find mechanisms by which diffusion-driven instabilities may arise even if the local interaction and movement rates do not indicate it.

Amazon islands as predator refugia: jaguar density and temporal activity in Maracá-Jipioca

AbstractLimited space on islands usually cannot sustain stable populations of large predators. However, jaguars, the largest cat species in the Americas, unexpectedly occur in the Estação Ecológica Maracá-Jipioca reserve, a system of continental Amazonian islands in the Atlantic Ocean. We investigated jaguar population structure, density, and activity patterns. We placed 25 camera-trap stations across 149.19 km2 and used spatially explicit capture–recapture to estimate density, and Rayleigh’s test to assess activity patterns. We identified 21 individuals (12 females, six males, and three cubs) and estimated an adult density of 6.7 individuals per 100 km2, which equals a population of approximately 43 jaguars. The population is composed mostly of females (66%) in relation to males (33%). Male and female activity patterns overlapped and showed more activity during daytime. The high jaguar density and the presence of females with cubs indicate that these islands are likely natural refugia for jaguars, reinforcing the importance of this protected area for jaguar conservation and possibly challenging the paradigm that large-mammal populations are not feasible in restricted islands.

Global carbon emission spatial pattern in 2030 under INDCs: using a gridding approach based on population and urbanization

PurposeThe intended nationally determined contributions (INDCs) is a major outcome of the Paris Agreement on international cooperation to reduce emissions, and is likely to be the future scenario for carbon emissions. This paper aims to obtain the fine spatial pattern of carbon emissions in 2030, identify hot spots and analyze changes of carbon emissions with a spatial grid method.Design/methodology/approachBased on the integrated quantified INDCs of each economy in 2030, the authors predict the population density pattern in 2030 by using the statistics of current population density, natural growth rates and differences in population growth resulting from urbanization within countries. Then the authors regard population density as a comprehensive socioeconomic indicator for the top-bottom allocation of the INDC data to a 0.1° × 0.1° grid. Then, the grid spatial pattern of carbon emissions in 2030 is compared with that in 2016.FindingsUnder the unconditional and conditional scenarios, the global carbon emission grid values in 2030 will be within [0, 59,200.911] ktCO2 and [0, 51,800.942] ktCO2, respectively; eastern China, northern India, Western Europe and North America will continue to be the major emitters; grid carbon emissions will increase in most parts of the world compared to 2016, especially in densely populated areas.Originality/valueWhile many studies have explored the overall global carbon emissions or warming under the INDC scenario, attention to spatial details is also required to help us make better emissions attributions and policy decisions from the perspective of the grid unit rather than the administrative unit.

Living on the edge: density and activity patterns of the ocelot, Leopardus pardalis, in the austral limit of the Atlantic Forest

ABSTRACT Knowledge on population density and activity patterns may help to understand how species with wide geographical distribution survive in different environments. The ocelot (Leopardus pardalis) is one of the neotropical felids with the greatest geographical range. We estimated the density and activity patterns of ocelots in the austral extreme of the species distribution (Southern Brazil), comparing our results with those of previous studies. We obtained ocelot records in three out of six sampled areas, but only two had sufficient records to estimate ocelot density. We estimated 15.5 (±6SE) and 27 (±24SE) individuals/100 km2 in two protected areas. These values seem low when compared to ocelots’ density estimates in other areas of the Atlantic Forest. In the most pristine area, density values were similar to those from a study carried out 10 years ago, suggesting that this population remains stable. Our results indicate that austral populations of the ocelot are likely to be dependent on preserved patches of deciduous seasonal forests. As in other areas of the species’ distribution, ocelots were mainly nocturnal, potentially avoiding humans and domestic animals. The preservation of those areas and the connectivity between them is a priority for the long-term conservation of stable ocelot´s populations in the southern Atlantic Forest range.

Understanding the Impact of Walkability, Population Density, and Population Size on COVID-19 Spread: A Pilot Study of the Early Contagion in the United States.

The novel coronavirus disease 2019 (COVID-19) pandemic is an unprecedented global event that has been challenging governments, health systems, and communities worldwide. Available data from the first months indicated varying patterns of the spread of COVID-19 within American cities, when the spread was faster in high-density and walkable cities such as New York than in low-density and car-oriented cities such as Los Angeles. Subsequent containment efforts, underlying population characteristics, variants, and other factors likely affected the spread significantly. However, this work investigates the hypothesis that urban configuration and associated spatial use patterns directly impact how the disease spreads and infects a population. It follows work that has shown how the spatial configuration of urban spaces impacts the social behavior of people moving through those spaces. It addresses the first 60 days of contagion (before containment measures were widely adopted and had time to affect spread) in 93 urban counties in the United States, considering population size, population density, walkability, here evaluated through walkscore, an indicator that measures the density of amenities, and, therefore, opportunities for population mixing, and the number of confirmed cases and deaths. Our findings indicate correlations between walkability, population density, and COVID-19 spreading patterns but no clear correlation between population size and the number of cases or deaths per 100 k habitants. Although virus spread beyond these initial cases may provide additional data for analysis, this study is an initial step in understanding the relationship between COVID-19 and urban configuration.

Which Gridded Population Data Product Is Better? Evidences from Mainland Southeast Asia (MSEA)

The release of global gridded population datasets, including the Gridded Population of the World (GPW), Global Human Settlement Population Grid (GHS-POP), WorldPop, and LandScan, have greatly facilitated cross-comparison for ongoing research related to anthropogenic impacts. However, little attention is paid to the consistency and discrepancy of these gridded products in the regions with rapid changes in local population, e.g., Mainland Southeast Asia (MSEA), where the countries have experienced fast population growth since the 1950s. This awkward situation is unsurprisingly aggravated because of national scarce demographics and incomplete census counts, which further limits their appropriate usage. Thus, comparative analyses of them become the priority of their better application. Here, the consistency and discrepancy of the four common global gridded population datasets were cross-compared by combing the 2015 provincial population statistics (census and yearbooks) via error-comparison based statistical methods. The results showed that: (1) the LandScan performs the best both in spatial accuracy and estimated errors, then followed by the WorldPop, GHS-POP, and GPW in MSEA. (2) Provincial differences in estimated errors indicated that the LandScan better reveals the spatial pattern of population density in Thailand and Vietnam, while the WorldPop performs slightly better in Myanmar and Laos, and both fit well in Cambodia. (3) Substantial errors among the four gridded datasets normally occur in the provincial units with larger population density (over 610 persons/km2) and a rapid population growth rate (greater than 1.54%), respectively. The new findings in MSEA indicated that future usage of these datasets should pay attention to the estimated population in the areas characterized by high population density and rapid population growth.

Seasonal Phenological Patterns and Flavivirus Vectorial Capacity of Medically Important Mosquito Species in a Wetland and an Urban Area of Attica, Greece.

Seasonal patterns of mosquito population density and their vectorial capacity constitute major elements to understand the epidemiology of mosquito-borne diseases. Using adult mosquito traps, we compared the population dynamics of major mosquito species (Culex pipiens, Aedes albopictus, Anopheles spp.) in an urban and a wetland rural area of Attica Greece. Pools of the captured Cx. pipiens were analyzed to determine infection rates of the West Nile virus (WNV) and the Usutu virus (USUV). The data provided were collected under the frame of the surveillance program carried out in two regional units (RUs) of the Attica region (East Attica and South Sector of Attica), during the period 2017–2018. The entomological surveillance of adult mosquitoes was performed on a weekly basis using a network of BG-sentinel traps (BGs), baited with CO2 and BG-Lure, in selected, fixed sampling sites. A total of 46,726 adult mosquitoes were collected, with larger variety and number of species in East Attica (n = 37,810), followed by the South Sector of Attica (n = 8916). The collected mosquitoes were morphologically identified to species level and evaluated for their public health importance. Collected Cx. pipiens adults were pooled and tested for West Nile virus (WNV) and Usutu virus (USUV) presence by implementation of a targeted molecular methodology (real-time PCR). A total of 366 mosquito pools were analyzed for WNV and USUV, respectively, and 38 (10.4%) positive samples were recorded for WNV, while no positive pool was detected for USUV. The majority of positive samples for WNV were detected in the East Attica region, followed by the South Sector of Attica, respectively. The findings of the current study highlight the WNV circulation in the region of Attica and the concomitant risk for the country, rendering mosquito surveillance actions and integrated mosquito management programs as imperative public health interventions.

Contrasting Adult Body-Size in Sister Populations of the Balearic Lizard, Podarcis lilfordi (Günther 1874) Suggests Anthropogenic Selective Pressures

Recently isolated populations offer a good biological model to infer the evolutionary forces responsible for the current divergences across populations. We coupled genetic, morphometric, ecological, and demographic analyses from three island populations of the endemic Balearic Wall Lizard, Podarcis lilfordi, (Balearic archipelago, Spain) to infer the mechanisms underlying the observed differences in body size. For each population, we described plant community structure, derived a biotic capacity index, and used individual-based data on 1369 lizards captured and released during 6 yr (2009–2015) to estimate population density and body growth patterns. We used genetic data collected on 80 individuals (∼27 for each population) to infer genetic divergences across islets and population history. Body size divergences cannot be explained by the ecological or population characteristics. Individual growth was slower in the smallest island, where lizards reached the largest average body size. In addition to having the highest density, results suggested that resource availability does not constrain asymptotic body size, but the speed at which individuals reach it does. The Approximate Bayesian Computation used to infer population history from genetic data supported the occurrence of two bottlenecks in the islet with the highest anthropogenic footprint. We emphasize the need to integrate ecological and genetic data and the importance of considering the effects of past human disturbance as an additional force in being able to model present island fauna.

Effects of large herbivores on fire regimes and wildfire mitigation

Abstract Abandonment of agricultural land is widespread in many parts of the world, leading to shrub and tree encroachment. The increase of flammable plant biomass, that is, fuel load, increases the risk and intensity of wildfires. Fuel reduction by herbivores is a promising management strategy to avoid fuel build‐up and mitigate wildfires. However, their effectiveness in mitigating wildfire damage may depend on a range of factors, including herbivore type, population density and feeding patterns. Here, we review the evidence on whether management with herbivores can reduce fuel load and mitigate wildfires, and if so, how to identify suitable management that can achieve fire mitigation objectives while providing other ecosystem services. We systematically reviewed studies that investigated links between herbivores, fire hazard, fire frequency and fire damage. We found that, in general, herbivores reduce fuel load most effectively when they are mixed feeders, when grazing and browsing herbivores are combined and when herbivore food preferences match the local vegetation. In some cases, the combination of herbivory with other management strategies, such as mechanical clearing, is necessary to reduce wildfire damage. Synthesis and Applications. We conclude that herbivores have the capacity to mitigate wildfire damage, and we provide guidance for grazing management for wildfire mitigation strategies. As areas undergoing land abandonment are particularly prone to wildfires, the maintenance or promotion of grazing by domestic or wild herbivores is a promising tool to reduce wildfire risk in a cost‐effective way, while also providing other ecosystem services. Relevant land‐use policies, including fire suppression policies, agricultural and forest(ry) policies could incentivise the use of herbivores for better wildfire prevention.

Growth of Greater White‐Fronted Goose Goslings Relates to Population Dynamics at Multiple Scales

ABSTRACTThe abundance of greater white‐fronted geese (Anser albifrons frontalis) on the Arctic Coastal Plain (ACP) of northern Alaska, USA, has more than tripled since the late 1990s; however, recent rate of annual population growth has declined as population size increased, which may indicate white‐fronted geese on the ACP are approaching carrying capacity. We examined rates of gosling growth in greater white‐fronted geese at 3 sites on the ACP during 2012–2014 to assist with predictions of future population trends and assess evidence for density‐dependent constraints on recruitment. We marked goslings at hatch with individually coded webtags and conducted brood drives during early August to capture, measure, and weigh goslings. Annual estimates of gosling mass at 32 days old (range = 1,190–1,685) indicate that goslings had obtained &gt;60% of asymptotic size. This rate of growth corresponds with that of other goose species and populations with access to high‐quality forage and no limitations on forage availability, and is consistent with the overall increase in abundance of white‐fronted geese at the ACP scale. Contrary to most previous investigations, age‐adjusted mass of goslings did not decline with hatch date. Goslings grew faster in coastal areas than at inland freshwater sites. Taken together, these findings suggest forage was not limiting gosling growth rates in either ecosystem, but forage was of greater quality in coastal areas where goose foraging habitat is expanding because of permafrost subsidence. Spatial patterns of gosling growth corresponded with local‐scale patterns of population density and population change; the areas with greatest rates of gosling growth were those with the greatest population density and rates of population increase. We found little evidence to suggest forage during brood rearing was limiting population increase of white‐fronted geese on the ACP. Factors responsible for the apparent slowing of ACP‐wide population growth are likely those that occur in stages of the annual cycle outside of the breeding grounds. Published 2021. This article is a U.S. Government work and is in the public domain in the USA.

Enhanced species coexistence in Lotka-Volterra competition models due to nonlocal interactions

We introduce and analyze a spatial Lotka-Volterra competition model with local and nonlocal interactions. We study two alternative classes of nonlocal competition that differ in how each species’ characteristics determine the range of the nonlocal interactions. In both cases, nonlocal interactions can create spatial patterns of population densities in which highly populated clumps alternate with unpopulated regions. These non-populated regions provide spatial niches for a weaker competitor to establish in the community and persist in conditions in which local models predict competitive exclusion. Moreover, depending on the balance between local and nonlocal competition intensity, the clumps of the weaker competitor vary from M-like structures with higher densities of individuals accumulating at the edges of each clump to triangular structures with most individuals occupying their centers. These results suggest that long-range competition, through the creation of spatial patterns in population densities, might be a key driving force behind the rich diversity of species observed in natural ecological communities.

Urban Growth and Heat in Tropical Climates

This research describes the change in temperatures across approximately 270 tropical cities from 1960 to 2020 with a focus on urban warming. It associates urban growth indicators with temperature variations in tropical climate zones (tropical rainforest, tropical monsoon, and tropical wet-dry savanna). Our findings demonstrate that over time while temperatures have increased across the tropics, urban residents have experienced higher temperatures (minimum and maximum) than those living outside of cities. Moreover, in certain tropical zones, over the study period, temperatures have risen faster in urban areas than the background (non-urban) temperatures. The results also suggest that with continuing climate change and urban growth, temperatures will continue to rise at higher than background levels in tropical cities unless mitigation measures are implemented. Several fundamental characteristics of urban growth including population size, population density, infrastructure and urban land use patterns are factors associated with variations in temperatures. We find evidence that dense urban forms (compact residential and industrial developments) are associated with higher temperatures and population density is a better predictor of variation in temperatures than either urban population size or infrastructure in most tropic climate zones. Infrastructure, however, is a better predictor of temperature increases in wet-dry savanna tropical climates than population density. There are a number of potential mitigation measures available to urban managers to address heat. We focus on ecological services, but whether these services can address the projected increasing heat levels is unclear. More local research is necessary to untangle the various contributions to increasing heat in cities and evaluate whether these applications can be effective to cool tropical cities as temperature continue to rise. Our methods include combining several different datasets to identify differences in daily, seasonal, and annual maximum and minimum temperatures.

POPULATION DISTRIBUTION AND DENSITY CHANGING PATTERN IN SUMATERA UTARA

The purpose of this study was to determine the distribution of population density descriptions and patterns of change in North Sumatra. This type of research is library research (Library Research). Data collection techniques are carried out by utilizing existing facilities in the library, such as books, magazines, documents, secondary data records, statistical data, or pure library research related to the object of research. The analytical method provides a clear, objective, systematic, analytical, and critical description and description of the distribution and population density description: characteristics and patterns of change in North Sumatra. The initial step is achieved by collecting the required data, classifying it, describing it, and then analyzing it. The results of this study explain that the distribution pattern and population density that occur are caused by spatial characteristics and geological changes. When viewed from the aspect of population density. The high population density in North Sumatra causes social problems such as congestion, poverty, health services, crime rates, settlements, unhealthy living environments, and others. The pattern of population distribution that occurs is geographical. The largest distribution is still throughout the East Coast region, wherein that region there are the largest number of districts (above 5% of the province's population).Keywords: Population, Distribution, Density, Spatial

Relationship of population migration, crop production pattern, and socioeconomic development: evidence from the early 21st century

Global crop production and population distributions have undergone great changes under climate change and socioeconomic development, and have drawn considerable public attention. How to explain the similarity of the migration patterns of crop yield and population density for different countries/regions is still uncertain and worth studying. Here, we estimated the similarity between migrations of main crop caloric yield (i.e. maize, rice, wheat, and soybean) and population density using Fréchet distance, and investigated the regression relationship between Fréchet distance and related climatic and socioeconomic variables for countries/regions with different economic development stages. The results indicated that different countries/regions showed different Fréchet distances during 2000–2015, with a maximum value of 24.44 for Russia and a minimum value of 0.11 for Georgia. For countries/regions with different economic development stages, the built regression models can explain 39%–93% of the variability in the Fréchet distance. Log(land area), log(GDP), and log(land area under cereal production) were always included in regression models and had higher importance in explaining the variability of Fréchet distance. For the model for all countries/regions, both the log(land area) and log(GDP per capita) may positively link to the Fréchet distance. Possible reasons for these results are that countries/regions with high GDP (or GDP per capita) may ease the conflict of land resources between humans and crops to achieve agricultural industrialization, which causes the far connection of the migrations for crop caloric yield and population density. The complicated interactions of crop production, population dynamic, and socioeconomic development should be given greater attention in the future.

To Pool or Not to Pool? Understanding opportunities, challenges, and equity considerations to expanding the market for pooling

On-demand mobility services such as bikesharing, scooter sharing, and transportation network companies (TNCs, also known as ridesourcing and ridehailing) are changing the way that people travel by providing dynamic, on-demand mobility that can supplement public transit and personal-vehicle use. Adoption of on-demand mobility has soared across the United States and abroad, driven by the flexibility and affordability that these services offer, particularly in urban areas where population density and land use patterns facilitate a reliable balance of supply and demand. The growth of app-based ridesharing, microtransit, and TNCs presents a unique opportunity to reduce congestion, energy use, and emissions through reduced personal vehicle ownership and increased vehicle occupancy, the latter of which is largely dependent on the decisions of individual travelers to pool or not to pool. This research provides key insights into the policy levers that could be employed to reduce vehicle miles traveled and emissions by incentivizing the use of pooled on-demand ride services and public transit. We employ a general population stated preference survey of four California metropolitan regions (Los Angeles, Sacramento, San Diego, and the San Francisco Bay Area) to examine the opportunities and challenges for drastically expanding the market for pooling, taking into account the nuances in emergent travel behavior and demand sensitivity across on-demand mobility options. Although high-frequency TNC users – those that use TNCs once a week or more - are more likely to consider pooling than less frequent users and reflect more multimodal travel behavior than other travelers, we find that the most captive and price sensitive TNC users are often the most vulnerable. Heavy TNC users – those using TNCs more than three days per week - are disproportionately low income, more likely not to own or lease a car and more likely to use TNCs for essential trip purposes than are less frequent users. Pooling demand sensitivity varies significantly across trip contexts, metropolitan regions, socio-demographics, travel behavior, and attitudes and perceptions toward sharing. We estimate the time and price tradeoffs in choosing between ride alone and shared on-demand service options, finding significant differences across values that travelers place on each component of travel time (wait time, access/egress walking time, and in-vehicle time) by geography and income level. We discuss the potential to leverage these insights to develop policies that combine pricing, curb management, and promotional strategies to increase the pooling market share.

REGIONAL VULNERABILITY TO DENGUE HEMORRHAGE FEVER (DHF) CASE IN PUSKESMAS MRANGGEN 3

Puskesmas Mranggen 3 (3rd Public Health Center of Mragen) area has DHF case annually. Environmental health factor is one of important indicators determining the health degree. This research aimed to find out the regional vulnerability index of DHF case. This study was an analytical observational research with spatial approach. The result of research showed that the regional vulnerability indexes of DHF case are 6.6% high, 32.9% moderate, and 14.5% low vulnerabilities. Regional vulnerability indexes without DHF case are 19.7% high, and 26.3% moderate vulnerabilities. Regional vulnerability results from the examination on house sanitation, larva free Index (LFI) and Container Index (CI), population density, and settlement pattern. Regional vulnerability Index in 76 RWs (neighbourhood associations in Puskesmas Mranggen 3 area can detect the areas with low, moderate, and high vulnerabilities in the region either with or without case; in addition, regional vulnerability is important to prevent and to control DHF case in micro scale.