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Preventive Medicine Reports Dec 2023Several factors related to hospitalizations, morbidity, and mortality from COVID-19 have been identified. However, limited exploration has been done on geographic and...
BACKGROUND
Several factors related to hospitalizations, morbidity, and mortality from COVID-19 have been identified. However, limited exploration has been done on geographic and socioeconomic factors that could significantly impact these outcomes.
OBJECTIVES
This study aimed to determine whether altitude, population density, and percentage of population in total poverty are associated with COVID-19 incidence per 1000 inhabitants and COVID-19 case-fatality rate in Peru, from 2020 to 2022.
METHODS
This study utilized a multiple group ecological design and relied on secondary databases containing daily records of COVID-19 positive cases and deaths due to COVID-19. An epidemiological analysis was performed, subsequently processed using a random effects model.
RESULTS
As of August 2022, Peru had recorded a total of 3,838,028 COVID-19 positive cases and 215,023 deaths due to COVID-19. Our analysis revealed a statistically significant negative association between altitude and COVID-19 incidence (aBETA: -0.004; Standard Error: 0.001; p < 0.05). Moreover, we observed a positive association between population density and incidence (aBETA: 0.006; Standard Error: 0.001; p < 0.05). However, we found no significant association between the percentage of population in total poverty and COVID-19 incidence.
CONCLUSION
Our study found that an increase in altitude was associated with a decrease in COVID-19 incidence, while an increase in population density was associated with an increase in COVID-19 incidence. High altitude, population density and percentage of population in total poverty does not change case-fatality rate due to COVID-19.
PubMed: 37753378
DOI: 10.1016/j.pmedr.2023.102423 -
Microbiology Spectrum Aug 2023The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was introduced in Algeria in March 2020. This...
The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was introduced in Algeria in March 2020. This study aimed to estimate the seroprevalence of SARS-CoV-2 infection in Oran, Algeria, and to identify factors associated with seropositivity. This was a cross-sectional seroprevalence study conducted between 7 and 20 January 2021 across all 26 municipalities in the province of Oran. The study employed a random cluster sampling technique stratified by age and sex to select participants from households, who were then administered a rapid serological test. The overall seroprevalence and specific seroprevalences by municipality were calculated, and the number of COVID-19 cases in Oran was estimated. The correlation between population density and seroprevalence was also examined. Among the participants, 422 (35.6%; 95% confidence interval [CI], 32.9 to 38.4) had a positive serological test for SARS-CoV-2, and eight municipalities had seroprevalence rates above 73%. We found a strong positive correlation between population density and seroprevalence ( = 0.795, < 0.001), indicating that areas with higher population density had higher numbers of positive COVID-19 cases. Our study provides evidence of a high seroprevalence of SARS-CoV-2 infection in Oran, Algeria. The estimated number of cases based on seroprevalence is much higher than the number of cases confirmed by PCR. Our findings suggest that a large proportion of the population has been infected with SARS-CoV-2, highlighting the need for continued surveillance and control measures to prevent further spread of the virus. This is the first and only seroprevalence study of COVID-19 conducted in the general population in Algeria prior to the national vaccination campaign against COVID-19. The significance of this study lies in its contribution to our understanding of the spread of the virus in the population before the implementation of the vaccination program.
Topics: Humans; COVID-19; SARS-CoV-2; Cross-Sectional Studies; Seroepidemiologic Studies; Pandemics; Antibodies, Viral
PubMed: 37284756
DOI: 10.1128/spectrum.00876-23 -
The Science of the Total Environment Jun 2024Accurate prediction of fluctuations of wildlife local number of individuals is crucial for effective population management to minimise human-wildlife conflicts. Climate,...
Accurate prediction of fluctuations of wildlife local number of individuals is crucial for effective population management to minimise human-wildlife conflicts. Climate, habitat, food availability, and density dependence are among the main factors influencing mammalian population dynamics. In southern Europe, precipitation and temperature, particularly during summer have been suggested as key factors affecting wild boar (Sus scrofa L.). However, there is uncertainty regarding the role of these factors and the mechanisms driving population fluctuations. This study utilized long-term data of wild boar populations from 14 study sites collected for 23 years in Catalonia, Spain, to analyse the factors that drive population density and growth rate. Generalized Additive Mixed Models (GAMM) explained respectively, 94 % and 65 % of the density and growth rate variability. Spring precipitation in both current and previous year, female weight, and forest cover (particularly above 60 %) were directly associated with higher wild boar densities and population growth rates. The interaction between crop cover and total annual precipitation also played a significant role in determining population density. Higher densities were linked to lower population growth in the following year, likely due to a density-dependent process. These results suggest that the expected decrease in rainfall linked with global warming may limit the availability of natural resources and potentially slow wild boar population growth. Nevertheless, wild boar can exploit alternative anthropogenic food sources, potentially leading to an increase of human-wildlife conflicts. Therefore, incorporating management policies aimed at restricting wild boar access to human food sources is key for controlling their reproductive output. Additionally, landscape management strategies targeted at diminishing refuge and resource availability in regions experiencing high wild boar impact are essential for contributing to sustainable coexistence between wild boars and human populations.
Topics: Animals; Sus scrofa; Spain; Population Density; Population Growth; Ecosystem; Population Dynamics; Animals, Wild; Conservation of Natural Resources
PubMed: 38697537
DOI: 10.1016/j.scitotenv.2024.172739 -
BMJ Military Health Nov 2023Terrorist events in the form of explosive devices have occurred and remain a threat currently to the population and the infrastructure of many nations worldwide.... (Review)
Review
Terrorist events in the form of explosive devices have occurred and remain a threat currently to the population and the infrastructure of many nations worldwide. Injuries occur from a combination of a blast wave, energised fragments, blunt trauma and burns. The relative preponderance of each injury mechanism is dependent on the type of device, distance to targets, population density and the surrounding environment, such as an enclosed space, to name but a few. One method of primary prevention of such injuries is by modification of the environment in which the explosion occurs, such as modifying population density and the design of enclosed spaces. The Human Injury Predictor (HIP) tool is a computational model which was developed to predict the pattern of injuries following an explosion with the goal to inform national injury prevention strategies from terrorist attacks. HIP currently uses algorithms to predict the effects from primary and secondary blast and allows the geometry of buildings to be incorporated. It has been validated using clinical data from the terrorist attacks in London and the 2017 Manchester Arena terrorist event. Although the tool can be used readily, it will benefit from further development to refine injury representation, validate injury scoring and enable the prediction of triage states. The tool can assist both in the design of future buildings and methods of transport, as well as the situation of critical emergency services required in the response following a terrorist explosive event. The aim of this paper is to describe the HIP tool in its current version and provide a roadmap for optimising its utility in the future for the protection of national infrastructure and the population.
Topics: Humans; Blast Injuries; Explosive Agents; Strategic Planning; Explosions; Terrorism
PubMed: 35241623
DOI: 10.1136/bmjmilitary-2021-002052 -
Trends in Ecology & Evolution Jun 2024Knowledge of ecosystem-size influences on river populations and communities is integral to the balancing of human and environmental needs for water. The multiple... (Review)
Review
Knowledge of ecosystem-size influences on river populations and communities is integral to the balancing of human and environmental needs for water. The multiple dimensions of dendritic river networks complicate understanding of ecosystem-size influences, but could be resolved by the development of scaling relationships. We highlight the importance of physical constraints limiting predator body sizes, movements, and population sizes in small rivers, and where river contraction limits space or creates stressful conditions affecting community stability and food webs. Investigations of the scaling and contingency of these processes will be insightful because of the underlying generality and scale independence of such relationships. Doing so will also pinpoint damaging water-management practices and identify which aspects of river size can be most usefully manipulated in river restoration.
Topics: Rivers; Ecosystem; Animals; Food Chain; Population Density; Population Dynamics
PubMed: 38388323
DOI: 10.1016/j.tree.2024.01.010 -
BMC Geriatrics Sep 2023Accurately predicting the future development trend of population aging is conducive to accelerating the development of the elderly care industry. This study constructed...
BACKGROUND
Accurately predicting the future development trend of population aging is conducive to accelerating the development of the elderly care industry. This study constructed a combined optimization grey prediction model to predict the structure and density of elderly population.
METHODS
In this paper, a GT-FGM model is proposed, which combines Theta residual optimization with fractional-order accumulation operator. Fractional-order accumulation can effectively weaken the randomness of the original data sequence. Meanwhile, Theta residual optimization can adjust parameter by minimizing the mean absolute error. And the population statistics of Shanghai city from 2006 to 2020 were selected for prediction analysis. By comparing with the other traditional grey prediction methods, three representative error indexes (MAE, MAPE, RMSE) were conducting for error analysis.
RESULTS
Compared with the FGM model, GM (1,1) model, Verhulst model, Logistic model, SES and other classical prediction methods, the GT-FGM model shows significant forecasting advantages, and its multi-step rolling prediction accuracy is superior to other prediction methods. The results show that the elderly population density in nine districts in Shanghai will exceed 0.5 by 2030, among which Huangpu District has the highest elderly population density, reaching 0.6825. There has been a steady increase in the elderly population over the age of 60.
CONCLUSIONS
The GT-FGM model can improve the prediction accuracy effectively. The elderly population in Shanghai shows a steady growth trend on the whole, and the differences between districts are obvious. The government should build a modern pension industry system according to the aging degree of the population in each region, and promote the balanced development of each region.
Topics: Humans; Aged; China; Aging; Logistic Models; Pensions
PubMed: 37716937
DOI: 10.1186/s12877-023-04197-2 -
Heliyon Mar 2024Reducing urban energy consumption is a crucial step towards achieving sustainable urban development. Urban energy plays a fundamental role in urban development, and...
Reducing urban energy consumption is a crucial step towards achieving sustainable urban development. Urban energy plays a fundamental role in urban development, and while previous studies have examined the relationship between population size and energy conservation, the impact of increasing population density on per capita energy consumption (PCEC) remains unclear. To achieve urban energy conservation in China, it is vital to comprehend this significant relationship. This study constructs a spatial regression model to examine the relationship between population density and PCEC using 9 years of balanced panel data from 276 cities to fill a gap in the literature. The results of spatial autocorrelation indicate a significant negative relationship and heterogeneity between population density and PCEC. The results of spatial regression show that for every 1% increase in population density, there is a subsequent increase in PCEC of 0.074%. Our findings suggest that lower PCEC correlation is associated with higher urban population density. This study can be a reference for policymakers seeking new energy conservation strategies for urban development.
PubMed: 38434365
DOI: 10.1016/j.heliyon.2024.e26882 -
PloS One 2023Large carnivores face numerous threats, including habitat loss and fragmentation, direct killing, and prey depletion, leading to significant global range and population...
Large carnivores face numerous threats, including habitat loss and fragmentation, direct killing, and prey depletion, leading to significant global range and population declines. Despite such threats, leopards (Panthera pardus) persist outside protected areas throughout most of their range, occupying diverse habitat types and land uses, including peri-urban and rural areas. Understanding of leopard population dynamics in mixed-use landscapes is limited, especially in South Africa, where the majority of leopard research has focused on protected areas. We use spatially explicit capture-recapture models to estimate leopard density across a mixed-use landscape of protected areas, farmland, and urban areas in the Overberg region of the Western Cape, South Africa. Data from 86 paired camera stations provided 221 independent captures of 25 leopards at 50 camera trap stations with a population density estimate of 0.64 leopards per 100 km2 (95% CI: 0.55-0.73). Elevation, terrain ruggedness, and vegetation productivity were important drivers of leopard density in the landscape, being highest on elevated remnants of natural land outside of protected areas. These results are similar to previous research findings in other parts of the Western Cape, where high-lying natural vegetation was shown to serve as both a refuge and a corridor for leopard movement in otherwise transformed landscapes. Given the low leopard density and the prevalence of transformed land intermixed with patches of more suitable leopard habitat, prioritising and preserving connectivity for leopards is vital in this shared landscape. Ecological corridors should be developed in partnership with private landowners through an inclusive and multifaceted conservation strategy which also incorporates monitoring of and rapid mitigation of emerging threats to leopards.
Topics: Animals; Panthera; South Africa; Anthropogenic Effects; Ecosystem; Population Density; Conservation of Natural Resources
PubMed: 37889916
DOI: 10.1371/journal.pone.0293445 -
Biological Reviews of the Cambridge... Oct 2023Monitoring on the basis of sound recordings, or passive acoustic monitoring, can complement or serve as an alternative to real-time visual or aural monitoring of marine... (Review)
Review
Monitoring on the basis of sound recordings, or passive acoustic monitoring, can complement or serve as an alternative to real-time visual or aural monitoring of marine mammals and other animals by human observers. Passive acoustic data can support the estimation of common, individual-level ecological metrics, such as presence, detection-weighted occupancy, abundance and density, population viability and structure, and behaviour. Passive acoustic data also can support estimation of some community-level metrics, such as species richness and composition. The feasibility of estimation and certainty of estimates is highly context dependent, and understanding the factors that affect the reliability of measurements is useful for those considering whether to use passive acoustic data. Here, we review basic concepts and methods of passive acoustic sampling in marine systems that often are applicable to marine mammal research and conservation. Our ultimate aim is to facilitate collaboration among ecologists, bioacousticians, and data analysts. Ecological applications of passive acoustics require one to make decisions about sampling design, which in turn requires consideration of sound propagation, sampling of signals, and data storage. One also must make decisions about signal detection and classification and evaluation of the performance of algorithms for these tasks. Investment in the research and development of systems that automate detection and classification, including machine learning, are increasing. Passive acoustic monitoring is more reliable for detection of species presence than for estimation of other species-level metrics. Use of passive acoustic monitoring to distinguish among individual animals remains difficult. However, information about detection probability, vocalisation or cue rate, and relations between vocalisations and the number and behaviour of animals increases the feasibility of estimating abundance or density. Most sensor deployments are fixed in space or are sporadic, making temporal turnover in species composition more tractable to estimate than spatial turnover. Collaborations between acousticians and ecologists are most likely to be successful and rewarding when all partners critically examine and share a fundamental understanding of the target variables, sampling process, and analytical methods.
Topics: Animals; Humans; Reproducibility of Results; Acoustics; Population Density; Mammals; Vocalization, Animal
PubMed: 37142263
DOI: 10.1111/brv.12969 -
Journal of Molecular Modeling Aug 2023Oligothiophenes have long been used as model compounds to understand the chemistry of polythiophenes. Herein, we have some quantum chemical calculations and intra- and...
CONTEXT
Oligothiophenes have long been used as model compounds to understand the chemistry of polythiophenes. Herein, we have some quantum chemical calculations and intra- and inter-molecular interaction calculations of a series of oligothiophenes such as terthiophene, quintetthiophene, sevensthiophene, terthiophene-terthiophene, terthiophene-water, terthiophene-methanol, and terthiophene-chloroform performed by time-dependent density functional theory (TD-DFT), density functional theory (DFT), and Multiwfn: a multifunctional wavefunction analyzer. The UV-vis spectra, HOMO-LUMO energies, NBO analysis, MEP, molecular structures, and electronic properties were computed using DFT/TD-DFT at the level of B3LYP/6-31+ G (d,p) and described. The nature of molecular interactions between terthiophene and solvents like water, methanol, and chloroform were also investigated using non-covalent interaction index (NCI), reduced density gradient (RDG), localized orbital locator (LOL), and electron localization function (ELF) topological analyses. Besides, Fukui functions and energy of population density-of-states were computed using the same method. The calculation results show that there are some changes in the terthiophene with the addition of solvent to the medium.
METHODS
DFT calculations were performed using the Gaussian 09 software and GaussView 5.0 visulation program. Multiwfn software is used to calculate the reduced density gradient (RDG) scatterplots, non-covalent interactions (NCI), ELF, LOL, Fukui analysis, and energy of population density-of-states of oligothiophenes.
PubMed: 37555864
DOI: 10.1007/s00894-023-05684-4