Endemic Caspian Sea mollusks in hotspot and non-hotspot areas differentially affected by anthropogenic pressures

Background: Dengue has affected more than one-third of the world population and Malaysia has recorded an increase in the number of dengue cases since 2012. Selangor state recorded the highest number of dengue cases in Malaysia. Most of the dengue infections occur among people living in hotspot areas of dengue. This study aims to compare Knowledge, Attitude, and Practice among communities living in hotspot and non-hotspot dengue areas. Method: Communities living in 20 hotspot and 20 non-hotspot areas in Selangor were chosen in this study where 406 participants were randomly selected to answer questionnaires distributed at their housing areas. Total marks of each categories were compared using t-test. Result: Results show that there were significant mean differences in marks in Knowledge (p value: 0.003; 15.41 vs. 14.55) and Attitude (p value: < 0.001; 11.41 vs. 10.33), but not Practice (p value 0.101; 10.83 vs. 10.47) categories between communities of non-hotspot and hotspot areas. After considering two confounding variables which are education level and household income, different mean marks are found to be significant in Knowledge when education level acts as a covariate and Attitude when both act as covariates. Conclusion: Overall results show that people living in non-hotspot areas had better knowledge and attitude than people living in hotspot areas, but no difference was found in practice. This suggests that public health education should be done more frequently with people with a low education background and low household income, especially in hotspot areas to fight dengue outbreak and make dengue cases decrease effectively.

Dengue fever is one of the most killer vectorborne disease in the world and Malaysia has recorded increases in number of dengue cases and deaths since 2012. For several years, Selangor state recorded the highest number of cases and deaths in Malaysia due to dengue fever. Most of the dengue infections occur among people who live in hotspot areas of dengue, and less likely to occur among people who live in non-hotspot areas. This study aims to compare the difference of environmental conditions between hotspot and non-hotspot areas of dengue. 20 hotspot and 20 non-hotspot areas in Selangor were chosen in this study and 10 variables were checked and given scale according to their conditions. Total marks of each area were then calculated and difference in means between hotspot and non-hotspot areas was compared using Independent T-test. Result shows that there was significant mean difference of marks of environmental conditions between both areas (p value: <0.001; 28.30 vs 22.90). The result of this study shows that non-hotspot areas were cleaner and more hygienic than hotspot areas, which suggests public health education and routine hygiene inspection to be done more frequently in hotspot areas to ensure their cleanliness in order to fight dengue outbreak, which consequently helps reduce the number dengue cases and deaths.

Undiagnosed tuberculosis (TB) cases are the major challenge to TB control in Nigeria. An early warning outbreak recognition system (EWORS) is a system that is primarily used to detect infectious disease outbreaks; this system can be used as a case-based geospatial tool for the real-time identification of hot spot areas with clusters of TB patients. TB screening targeted at such hot spots should yield more TB cases than screening targeted at non-hot spots. We aimed to demonstrate the effectiveness of an EWORS for TB hot spot mapping as a tool for detecting areas with increased TB case yields in high TB-burden states of Nigeria. KNCV Tuberculosis Foundation Nigeria deployed an EWORS to 14 high-burden states in Nigeria. The system used an advanced surveillance mechanism to identify TB patients' residences in clusters, enabling it to predict areas with elevated disease spread (ie, hot spots) at the ward level. TB screening outreach using the World Health Organization 4-symptom screening method was conducted in 121 hot spot wards and 213 non-hot spot wards selected from the same communities. Presumptive cases identified were evaluated for TB using the GeneXpert instrument or chest X-ray. Confirmed TB cases from both areas were linked to treatment. Data from the hot spot and non-hot spot wards were analyzed retrospectively for this study. During the 16-month intervention, a total of 1,962,042 persons (n=734,384, 37.4% male, n=1,227,658, 62.6% female) and 2,025,286 persons (n=701,103, 34.6% male, n=1,324,183, 65.4% female) participated in the community TB screening outreaches in the hot spot and non-hot spot areas, respectively. Presumptive cases among all patients screened were 268,264 (N=3,987,328, 6.7%) and confirmed TB cases were 22,618 (N=222,270, 10.1%). The number needed to screen to diagnose a TB case in the hot spot and non-hot spot areas was 146 and 193 per 10,000 people, respectively. Active TB case finding in EWORS-mapped hot spot areas yielded higher TB cases than the non-hot spot areas in the 14 high-burden states of Nigeria. With the application of EWORS, the precision of diagnosing TB among presumptive cases increased from 0.077 to 0.103, and the number of presumptive cases needed to diagnose a TB case decreased from 14.047 to 10.255 per 10,000 people.

Assessment of PCBs and exposure risk to infants in breast milk of primiparae and multiparae mothers in an electronic waste hot spot and non-hot spot areas in Ghana

BackgroundRabies remains a significant public health concern in Nigeria, particularly in rural areas with limited awareness and resources. Gombe State is recognized as a rabies hotspot, facing challenges in controlling the spread of the disease. This study aimed to assess and compare the knowledge and prevention practices related to rabies among community members in hotspot and non-hotspot areas of Gombe State.MethodsA community-based comparative cross-sectional study was conducted in Gombe State. Multistage sampling technique was used to select 816 eligible respondents from selected households with pet dogs or cats (408 each from hotspot and non-hotspot areas). A semi-structured, pre-tested digital interviewer-administered questionnaire was used to collect data on socio-demographics, rabies knowledge, and prevention practices. Data were analyzed using SPSS version 26. The univariate and bivariate analysis compared rabies knowledge and prevention practices at p value < 0.05. Logistic regression identified predictors of good practice.ResultsRespondents from hotspot areas demonstrated better overall knowledge of rabies compared to those from non-hotspot areas. However, a higher proportion of respondents from non-hotspot areas exhibited better rabies prevention practices, particularly in terms of vaccinating their dogs within the previous year. Factors such as older age (AOR: 0.47, 95% CI: 0.27– 0.84), farming occupation (AOR: 0.48, 95% CI: 0.27 – 0.84), and good overall rabies knowledge (AOR: 3.04, 95% CI: 1.37 – 6.73) were significant predictors of rabies prevention practices in the hotspot area.ConclusionTargeted educational interventions and tailored prevention strategies are needed to improve rabies awareness and practices, especially among specific demographic groups like older individuals and farmers. Enhancing overall knowledge of rabies and promoting consistent vaccination practices for pets are crucial steps towards reducing the incidence of rabies in both hotspot and non-hotspot areas.

Dengue fever is a deadly vector-borne disease. Prevention strategies without specific drugs or vaccines emphasise community involvement in dengue vector control. Identifying dengue-related knowledge, attitudes, and behaviours is critical to developing more effective intervention strategies. A cross-sectional study compared the knowledge, attitudes, and practices on dengue in selected dengue hotspots and non-hotspot areas in Selangor, Malaysia. A self-administered questionnaire was distributed among 320 randomly selected residents. Data were analysed using an independent t-test and Spearman’s rank-order correlation. Despite having a good understanding of the dengue virus, most respondents (83.1%) from both hotspot and non-hotspot areas were unaware that a person could be infected with the virus more than once in their lifetime, and 62.8% agreed that dengue patients could recover without treatment. Most respondents (76.9%) agreed that buying mosquito repellent is a waste of money, and most reported not sleeping under the insecticide net at night (74.7%). Respondents from dengue hotspot areas had significantly higher attitude scores (32.00±4.60) compared to those of non-hotspot regions (28.78±5.51), t (307) = 5.674, &lt;i&gt;p&lt;/i&gt;&lt;0.05. There was a significant positive correlation between knowledge and attitude scores (r&lt;sub&gt;s&lt;/sub&gt;=0.214, p&lt;0.01), between knowledge and practices (r&lt;sub&gt;s&lt;/sub&gt;=0.563, p&lt;0.01), and attitude and practices (r&lt;sub&gt;s&lt;/sub&gt;=0.374, p&lt;0.01). In addition to the high levels of knowledge and practice, attitudes toward dengue must be improved to implement proper prevention measures.

Differential impact of anthropogenic pressures on Caspian Sea ecoregions

Falls in the home and community environments are the leading cause of injuries and long-term disabilities for the aging population. This study examines the outcomes of a partnership among an academic institution, government agency, community nonprofit, and emergency services organization to expand access to a fall prevention training program by targeting delivery in postal codes identified as underserved with high rates of falls emergencies (hot spots) and non-high rates (non-hot spots). A total of 354 adults aged 50 and older participated in a fall prevention education program, with 188 (53%) participants completing at least five sessions (completers), of which 35% resided in hot spot areas. Descriptive statistics for frequency, percentage, mean, and standard deviations values were calculated for demographic variables. A paired t-test analysis was conducted to compare initial and final scores for self-assessed general health and fall efficacy programs. The paired sample t-test statistics revealed significant improvements in fall efficacy for completers in hot spots (t= -6.23; p < 0.001) and non-hot spots areas (t= - 11.17; p < 0.001). No statistical differences (p > 0.05) were observed between the initial and final scores of the self-assessed general health for completers in hot spots and non-hot spot areas. Cross-sector collaboration to deliver targeted falls prevention training at various community locations can effectively reach underserved, at-risk older adults, although additional retention strategies must be considered. In conclusion, identifying at-risk older adults to mobilize partnerships, limited resources can be allocated towards improving retention and program outcomes of community-based fall prevention education.

Maximizing crime prevention through large-scale implementation of hot spot policing requires a more refined understanding of how to calibrate police activity across high and low-risk areas. This study investigates these issues based on the experience of a large urban police agency that substantially reduced proactive activities across a large area due to resource cutbacks while also shifting a larger share of its declining proactive work into prioritized micro hot spots. Time series models were used to estimate the effects of these changes on crime-related calls in hot spots and non-hot spot areas. Hot spots required higher levels of proactivity (expressed as rates per day or per crime) to control crime, and serious crime rose in these locations following modest reductions in proactivity. In areas outside hot spots, minor and property crimes rose, but only after reductions of one-half to two-thirds in proactive work. Violence was unaffected in these areas, and they did not experience accelerated growth in crime relative to prioritized hot spots. These results help to illuminate minimum levels of police activity that may be necessary to control crime in places of varying risk. They also suggest that police can reduce proactive work by substantial amounts in lower risk areas to place more emphasis on hot spots. Better understanding of these issues is central to widespread, systematic operationalization of hot spot policing as a means to reduce crime across large areas.

Abstract. During the last decades, the coastal areas of the Kingdom of Saudi Arabia, on the Red Sea and the Arabian Gulf, have been subjected to intense economic and industrial growth. As a result, it may be expected that the overall environmental status of Saudi Arabian coastal marine waters has been affected by human activities. As a consequence, adequate management of the Saudi Arabian coastal zone requires an assessment of how the various pressures within this zone impact the quality of seawater and sediments. To this end, environmental surveys were conducted over 15 hotspot areas (areas subject to environmental pressures) in the Saudi Arabian coastal zone of the Red Sea and over three hotspot areas in the Saudi Arabian waters of the Arabian Gulf. The survey in the Red Sea, conducted in June/July 2021, acquired measurements from hotspot areas spanning most of the Saudi coastline, extending from near the Saudi–Jordanian border in the north to Al Shuqaiq and Jizan Economic City (close to the Saudi–Yemen border) in the south. The survey in the Arabian Gulf, carried out in September 2021, included the areas of Al Khobar, Dammam and Ras Al Khair. The main objective of both cruises was to record the physical and biogeochemical parameters along the coastal waters of the kingdom, tracing the dispersion of contaminants related to specific pressures. Taken together, these cruises constitute the first multidisciplinary and geographically comprehensive study of contaminants within the Saudi Arabian coastal waters and sediments. The measurements acquired revealed the influence of various anthropogenic pressures on the coastal marine environment of Saudi Arabia and also highlighted a strong influence of hydrographic conditions on the distribution of biochemical properties in the Red Sea and the Arabian Gulf. The data can be accessed at SEANOE https://doi.org/10.17882/96463 (Abualnaja et al., 2023), whereas the details of the sampling stations are available at https://mcep.kaust.edu.sa/cruise-postings (last access: 25 March 2024). The dataset includes the parameters shown in Tables 1a, b and 2a.

Regular samplings of two important vectors in farmers' fields were made at crop stages susceptible to rice yellow mottle virus on a traditional rice variety (Supa) under rainfed lowland conditions to provide information on the dynamic nature of the disease and the bionomics and importance of vectors in the disease transmission. The population of an unknown Chaetocnema sp. was significantly higher in hotspot than non-hotspot areas. However, there was no significant difference in C. pulla Chapuis population between both areas. In general the unkown Chaetcnema sp. population was higher than C. pulla, and both vectors reached the peak of their population at 63 days after planting. Also, early planting in the hotspot areas is suggested as a disease management strategy.

In this paper, a Per-Hop Acknowledgement (PHACK)-based scheme is proposed for each packet transmission to detect selective forwarding attacks. In our scheme, the sink and each node along the forwarding path generate an acknowledgement (ACK) message for each received packet to confirm the normal packet transmission. The scheme, in which each ACK is returned to the source node along a different routing path, can significantly increase the resilience against attacks because it prevents an attacker from compromising nodes in the return routing path, which can otherwise interrupt the return of nodes’ ACK packets. For this case, the PHACK scheme also has better potential to detect abnormal packet loss and identify suspect nodes as well as better resilience against attacks. Another pivotal issue is the network lifetime of the PHACK scheme, as it generates more acknowledgements than previous ACK-based schemes. We demonstrate that the network lifetime of the PHACK scheme is not lower than that of other ACK-based schemes because the scheme just increases the energy consumption in non-hotspot areas and does not increase the energy consumption in hotspot areas. Moreover, the PHACK scheme greatly simplifies the protocol and is easy to implement. Both theoretical and simulation results are given to demonstrate the effectiveness of the proposed scheme in terms of high detection probability and the ability to identify suspect nodes.

This paper starts from the observation that development projects that create various forms of environmental injustice in Europe are an integral part of the process of biospheric expulsions, that is of pushing out groups from adequate land, water or air, as described by Saskia Sassen (2014). Apart from the environmental, socio-economic and health-impacts of ecologically destructive projects, there is an added dimension of concern that has been less obvious in the past, but tends to become increasingly pronounced in a warming world. Is it possible that accumulating environmental inequalities and forms of injustice can create new and “unnatural” vulnerabilities to the projected climate change impacts? The first question that we tackle is whether environmental justice conflicts in Europe tend to take place disproportionately in climate hotspot areas, which are geographic spaces with above-average social sensitivity, potential vulnerability, potential social impact, potential environmental impacts or response capacity (ESPON, 2011). The second question concerns the distribution of different characteristics of projects and of their associated conflicts in climate hotspot vs. non-hotspot areas. The final goal is to establish, at a preliminary level, the emergence of a climate edge in Europe, a spatial configuration in which vulnerability to climate change impacts is shaped by processes of biospheric expulsion, as postulated at a general level by Sassen. For the analysis, the most current data on environmental justice conflicts (444) from the Environmental Justice Atlas and ESPON climate impact projections, mapped on the Climate Adapt platform, are used. The expected result is to provide a preliminary description of the postulated climate edge.

BackgroundNoroviruses are a leading cause of acute gastroenteritis (AGE) worldwide. The geographical characteristics of norovirus outbreaks in Beijing and their influencing factors remain unknown. This study aimed to explore the spatial distributions, geographical characteristics, and influencing factors of norovirus outbreaks in Beijing, China.MethodsEpidemiological data and specimens were collected through the AGE outbreak surveillance system in all 16 districts of Beijing. Data on spatial distribution, geographical characteristics, and influencing factors of norovirus outbreaks were analyzed using descriptive statistics methods. We measured spatial, geographical clustering of high- or low-value deviance from random distribution using Z-scores and P-values as statistical significance measures with Global Moran’s I statistics and Getis-Ord Gi in ArcGIS. Linear regression and correlation methods were used to explore influencing factors.ResultsBetween September 2016 and August 2020, 1,193 norovirus outbreaks were laboratory-confirmed. The number of outbreaks varied seasonally, typically peaking in spring (March to May) or winter (October to December). Outbreaks primarily occurred around central districts at the town level, and spatial autocorrelation was evident in both the entire study period and in individual years. Hotspots of norovirus outbreaks in Beijing were primarily found in contiguous areas between three central districts (Chaoyang, Haidian, Fengtai) and four suburban districts (Changping, Daxing, Fangshan, Tongzhou). The average population numbers, mean number of all schools, and mean number of kindergartens and primary schools for towns in central districts and hotspot areas were higher than those in suburban districts and non-hotspot areas respectively. Additionally, population numbers and densities of kindergartens and primary schools were influencing factors at the town level.ConclusionsHotspots of norovirus outbreaks in Beijing were in contiguous areas between central and suburban districts with high populations, and high kindergarten and primary school densities were the likely driving forces. Outbreak surveillance needs to focus on contiguous areas between central and suburban districts with increased monitoring, medical resources, and health education.

We propose a novel event data collection approach named reliability and multipath encounter routing (RMER) for meeting reliability and energy efficiency requirements. The contributions of the RMER approach are as follows. 1) Fewer monitor nodes are selected in hotspot areas that are close to the Sink, and more monitor nodes are selected in nonhotspot areas, which can lead to increased network lifetime and event detection reliability. 2) The RMER approach sends data to the Sink by converging multipath routes of event monitoring nodes into a one-path route to aggregate data. Thus, energy consumption can be greatly reduced, thereby enabling further increased network lifetime. Both theoretical and experimental simulation results show that RMER applied to event detection outperforms other solutions. Our results clearly indicate that RMER increases energy efficiency by 51% and network lifetime by 23% over other solutions while guaranteeing event detection reliability.