Population Movements Research Articles

Trophy fish heads are a source of body size information for historical and contemporary ecology

Abstract This study investigated whether trophy taxidermy specimens of Australia’s largest freshwater fish, Murray cod (Maccullochella peelii), can provide accurate records of historical body size. Taxidermy mounts came mostly from informal collections in hotels from across the Murray–Darling Basin, south-eastern Australia, comprising 20% whole-body and 80% head forms. We compared the morphology of mounts to live Murray cod, collected from the mid–Murray River in 2018, and identified the head morphometrics that most accurately described length and weight of whole mounts and live fish. Eight morphological characters were analysed for 60 whole mounts, 172 head mounts and 51 live fish. We found that inter-orbital distance, inter-nare width and upper jaw length were relatively robust to taxidermy processes and were reliable features for predicting fish total length and total weight. Shrinkage in head morphometrics due to taxidermy was evident, however, and we recommend that this be considered when reconstructing length and weight measures. We discuss how estimated body length and weight from head morphometrics of trophy fish, coupled with analysis of the accompanying remaining tissue and hard parts, opens up opportunities to explore patterns in genetics, life history, movement and trophic ecology of historical fish populations and of past environments.

Contribution of Travelers to Plasmodium Vivax Malaria in South West Delhi, India: Cross-Sectional Survey.

India is committed to malaria elimination by the year 2030. According to the classification of malaria endemicity, the National Capital Territory of Delhi falls under category 1, with an annual parasite incidence of <1, and was targeted for elimination by 2022. Among others, population movement across states is one of the key challenges for malaria control, as it can result in imported malaria, thus introducing local transmission in an area nearing elimination. This descriptive study attempts to assess the contribution of such imported Plasmodium vivax cases to the malaria burden in South West Delhi (SWD). A cross-sectional study was carried out at the fever clinic of the Indian Council of Medical Research-National Institute of Malaria Research in SWD from January 2017 to December 2019. Demographic and travel history data were recorded for all P vivax confirmed malaria cases diagnosed at the fever clinic. Vector and fever surveys along with reactive case detection were conducted in SWD and Bulandshahr district of Uttar Pradesh, 1 of the 6 geographical sources for a high number of imported malaria cases. A total of 355 P vivax malaria cases were reported during the study period. The proportion of imported cases was 63% (n=222). Of these, 96% (n=213) of cases were from Uttar Pradesh. The distribution of malaria cases revealed that imported cases were significantly associated with travel during the transmission season compared with that in the nontransmission season. Entomological and fever surveys and reactive case detection carried out in areas visited by imported P vivax malaria cases showed the presence of adults and larvae of Anopheles species and P vivax parasitemia. Population movement is a key challenge for malaria elimination. Although additional P vivax infections and vector mosquitoes were detected at places visited by the imported malaria cases, the inability to detect the parasite in mosquitoes and the possibility of relapses associated with P vivax limit the significance of malaria associated with the travel. However, there remains a need to address migration malaria to prevent the introduction and re-establishment of malaria in areas with very low or 0 indigenous cases.

Impact of Government Healthcare Policy Changes on Consumption and Human Movements During COVID-19: An Interrupted Time Series Analysis in Korea.

The coronavirus disease 2019 (COVID-19) pandemic has altered daily behavioral patterns based on government healthcare policies, including consumption and movement patterns. We aimed to examine the extent to which changes in the government's healthcare policy have affected people's lives, primarily focusing on changes in consumption and population movements. We collected consumption data using weekly credit card transaction data from the Hana Card Corporation and population mobility data using mobile phone data from SK Telecom in Seoul, South Korea. Interrupted time-series analysis was used to calculate the relative risk ratio and perform the intervention effects when government healthcare policy changes. We found that leisure and outside movements were the most immediately affected by changes in government healthcare policies. It took over 2 years and 11 months, respectively, for these sectors to return to their pre-COVID-19 routines. Enhancing healthcare policies presents advantages and disadvantages. Although such policies help prevent the spread of COVID-19, they also reduce consumption and mobility, extending the time needed to return to pre-COVID-19 levels. Government healthcare policymakers should consider not only disease prevention but also the impact of these policies on social behaviors, economic activity, and mobility.

Labor Market Conditions and Labor Migration in Russian Regions

In recent years, the Russian labor market has been in an extremely tense state, close to “overheating,” which poses risks for the economic development of the country. The most dynamically changing components of the market are the demand for labor and its supply. In the context of population decline, migration remains a flexible and effective mechanism for replenishing the labor force. Differences in the demographic and socio-economic situation in the Russian Federation and neighboring countries, primarily Central Asian ones, create preconditions for cross-border population movements, while the differentiation of various indicators of Russian regions becomes a factor in intra-country migration. In this study, the authors set the task of assessing the extent to which the situation in regional labor markets can influence the intensity of both international and interregional migration flows in Russia, ensuring their self-regulation and balancing. For this purpose, we constructed a clustering of the subjects of the Russian Federation based on the main indicators of labor supply and demand, as well as the intensity of labor migration flows in various directions. Then a correlation analysis of the selected indicators was carried out. The results show that, in general, labor migration smooths out imbalances in regional markets, but the effect of self-regulation mechanisms is far from perfect. For example, there is no linear relationship between tension in the labor market and the intensity of arrival of labor migrants. Based on the findings, the authors conclude by making recommendations regarding the need to create and improve federal mechanisms to ensure contact between employers and job seekers from different regions and to stimulate labor mobility of their populations.

Solving the challenges of interpolating NO&lt;sub&gt;2&lt;/sub&gt; from SPRINT data and modelling population movements in agent-based modelling

This study addresses two critical challenges in urban air quality exposure simulation and offers solutions. The first challenge is to generate nitrogen dioxide (NO2) fields across the city of London from available stations that provide Spatially Poor but Rich In Time (SPRINT) data. We first used Inverse Distance Weighting (IDW) to spatially interpolate NO2 at each half-a-day step. Each station had a list of hourly NO2 values for each time step, from which one NO2 value was selected by a stochastic process to generate the field. We also added weightings of up to a factor of 3 to London's NOx emissions to account for emissions from sources other than vehicles. We cross-validated the modelled data with the station data and found beta parameter of 1.5 to be the most appropriate 'power' parameter. The second challenge investigated the use of a fractional origin-destination (OD) matrix to see how to overcome errors when assigning destinations to a small set of population. We tested that ‘the nested bin strategy’ worked well for our 6,078 London resident agents. To enrich the dynamics to represent people’s non-work mobility patterns, we included visits to recreational areas during weekends and festive periods. This, in turn, provides a more comprehensive representation of urban mobility. Solutions to each challenge can provide more accurate assessments of pollution exposure, leading to better informed public health interventions.

Urban traffic accidents in Isfahan city: a study of prehospital response time intervals

IntroductionTraffic accidents are a major public health concern worldwide, resulting in significant injuries, fatalities, and economic costs. In urban zones, traffic accident dynamics can vary significantly due to population density, infrastructure, and emergency response capabilities. The present study was conducted to determine the time intervals of prehospital emergencies in traffic accidents by separating the 15 zones of Isfahan city, Iran.MethodsThis descriptive study was conducted in 2023. The sampling approach involved a census that included all prehospital emergency missions that occurred in the second half of 2022. A total of 7613 missions were examined. To collect the data, a checklist covering demographic characteristics and mission-specific features was utilized. The information was recorded in an Excel spreadsheet and described via the prehospital emergency information system.ResultsAfter analyzing 7,613 urban missions, it was determined that Zone 12 had the highest number of prehospital emergency missions in all three time periods: morning, afternoon, and evening. Therefore, all the times (reaction time, response time, scene time, transfer time, and hospitalization time) were in accordance with prehospital emergency time standards in Iran.ConclusionOn the basis of the findings of this study, it is crucial to identify zones with greater population movement, highways, or high traffic volume and establish bases in suitable locations whenever feasible. Additionally, in zones with a greater number of missions, there should be an appropriate number of ambulances in proportion to the mission volume.

Moscow Population Before and After the COVID-19 Pandemic

Background. Moscow managed to overcome the challenges of the COVID-19 pandemic by increasing the efforts of the healthcare system and maintaining the birth rate. As a result, the population growth in Moscow remained steady. Like any metropolis, Moscow faces the issue of an aging population, largely due to increased life expectancy, which presents significant challenges for sustainable societal development.Objective. To evaluate the size, composition, and structure of the Moscow population before and after the COVID-19 pandemic.Materials and methods. The authors used the official population data from the Federal State Statistics Service of the Russian Federation (ROSSTAT) and demographic information from the Moscow and Moscow Oblast offices of ROSSTAT (MOSSTAT), focusing on age and gender distributions across municipal areas. The results were visually represented using cartographic tools from the Integrated Data Warehouse of the Information and Analytical System for Comprehensive Development Monitoring in Moscow.Results. In 2021, Moscow's population experienced a decline primarily due to the significant negative effects of the COVID-19 pandemic. However, the number of residents began to increase again afterward. The Moscow population reduced only in 2021 due to the tremendous, negative impact of the COVID-19 pandemic, then the growth in the number of residents recovered. The analysis of the Moscow population pyramid demonstrated a substantial shift towards the older generations. On average, the population of Moscow is two years older than that of the Russian Federation as a whole.Discussion. The demographic landscape of Moscow underwent substantial changes during the pandemic due to complex dynamics in demographic processes. High rates of morbidity and mortality from COVID-19 led to a temporary decrease in the Moscow population and altered natural population movement indicators.Conclusion. Studying the impact of the COVID-19 pandemic on the population size and structure helps to forecast long-term consequences for health and the demographic situation in Moscow. This understanding is essential for developing the relevant improvement programs.

Ancient DNA: a direct window into the human past

The origin and history of our species have for long captured our imagination and guided philosophical and scientific inquiry alike. Traditionally, the study of the human past was a central theme of various disciplines across the humanities, in particular history, archaeology, anthropology, or linguistics. These disciplines mostly focus on understanding the roots and cultural evolution of contemporary human populations, including the plethora of religions, ethnicities, behaviours, and languages that characterize the diversity of human life on the planet. Recently, a technological revolution in molecular biology, which made it possible to obtain genetic material from biological remains and cultural artefacts unearthed at archaeological sites and stored in museum collections, has provided unparalleled information on the biological history of past human populations. Over the last decade, ancient DNA emerged as a crucial tool for understanding human origins, population movement, or environmental adaptation. The exponential growth in ancient DNA studies makes cooperative, transdisciplinary research efforts imperative to enable appropriate integration of knowledge across complementary scientific disciplines. These transdisciplinary approaches are particularly relevant for studying the recent human past, where the higher availability of historical, archaeological, anthropological, and linguistic data can successfully allow for meaningful interpretations of the genetic data.

Population shifts during the reconstruction period in areas marked as evacuation zones after the Fukushima Daiichi nuclear power plant accident: a mobile spatial statistics data-based time-series clustering analysis.

An accurate understanding of the population is essential for the development of medical care and social resources. However, the development of transportation networks has increased temporal and spatial fluctuations in the population, making it difficult to accurately forecast medical care demand, especially during disaster recovery. This study examined the population movement in areas affected by the Fukushima Daiichi nuclear power plant accident using demographic data. The target area includes two cities, seven towns, and three villages that are in the evacuation zone. Using a population estimation that reflects changes in population by time of day, which was obtained from a mobile phone company (NTT DOCOMO), we applied clustering analysis to examine the population dynamics over a 4-year period. From 2019 to 2022, the population increased in eight areas and decreased in four areas. The population was further classified into five groups, identifying the unique characteristics and fluctuations of each group. Different regions had different percentages of groups reflecting the characteristics of their populations. The differences among the regions and demographic transition showed the potential to understand the challenges of recovery and to use the data to inform healthcare planning and social policies. This method, which utilizes estimated population data, is also applicable to the study of medical resources and social policies in the event of future disasters and may be useful in analyzing regional characteristics in detail.

Changes in the Economic Behaviour of Czech Households in the Years of Economic Crisis and Pandemic

In the period following 2000, the Czech economy went through two crises, which were different in their causes, durations and consequences. The 2009–2013 crisis resulted from the global financial and fiscal crisis. Its causes were external and purely economic, and its impact on households' economic behaviour was 'standard' – a gradual and moderate reduction in consumption and investment with high unemployment and low inflation rates. The advent of the COVID-19 pandemic in 2020 meant a sudden and unexpected change in economic conditions – the closure of shops and services, restricted population movements, and household consumption limited to only the most essential products. A reduction in household consumption generally means an increase in household savings if all other circumstances are equal. The aim of the present paper is to show, using the methods of time series analysis, the effects of these two crisis periods in terms of data for the household sector or to show whether the fall in the propensity to consume and the rise in the propensity to save in 2020–2021 can be considered statistically significant compared to the crisis period of 2009–2013. Publicly available data from the Czech Statistical Office have been used for our analysis.

Seasonal Migratory Activity of the Beet Armyworm Spodoptera exigua (Hübner) in the Tropical Area of China.

The beet armyworm Spodoptera exigua (Hübner), a global pest, feeds on and affects a wide range of crops. Its long-distance migration with the East Asian monsoon frequently causes large-scale outbreaks in East and Southeast Asia. This pest mainly breeds in tropical regions in the winter season every year; however, few studies have investigated associations with its population movements in this region. From 2017 to 2023, we monitored its population dynamics in a tropical site, located in Hainan Province of China, using a searchlight trap. Dissection of the ovaries of female S. exigua moths captured from the air revealed that most of them were reproductively mature and could be classified as a transit migratory population. Migration occurred most often in summer and least often in winter, with an increasing trend over the years. According to a trajectory model analysis based on the Weather Research and Forecasting (WRF) model, S. exigua migrated from Hainan Island to mainland China in the spring, primarily moved from the areas of Southeast Asia to Hainan and mainland China during the summer, and returned from China to Southeast Asia in the autumn and winter. Overall, our research defines the movement paths of S. exigua in the tropical area of China, establishing a theoretical foundation for its regional monitoring, early warning, and management in China and Southeast Asian countries.

Settlement-level economic performance as a factor influencing working-age population migration in South Africa

ABSTRACT South African towns and cities face substantial challenges, owing largely to the pace of economic growth to date and continued migration of people from rural areas. The widely accepted push–pull theory of migration assumes that migration is a functional and inevitable outcome of spatial inequality. Economic drivers are frequently used to explain population movements in South Africa, given that the country’s biggest socio-economic challenges include high unemployment, stark inequality and persistent poverty. This study empirically investigates the theoretical perspective of the push–pull model from an economic and settlement-based standpoint. It establishes a settlement-level perspective of the relationship between economic performance and working-age population change in South Africa between the 2001 and 2011 Censuses. Fine-resolution downscaled economic and population datasets are used, applying spatial GIS-based methods and techniques, together with statistical correlation analyses, to explore and quantify the relationship. Population change in the working-age population is found to have a positive statistically significant association with economic performance at settlement level. The relationship is multifaceted, given the complexity of South Africa’s economic and development landscape, with considerable variability between different economically profiled settlement types, and different demographic groups based on age, gender, employment status and skills level.

Spatiotemporal changes in the congestion index of streets and roads in the armed conflict conditions

This article examines the impact of war on the formation of urban transport flows. During armed conflicts, the transport infrastructure of cities undergoes significant changes, which greatly affects the mobility and safety of the population. The need to study this issue is particularly relevant in the context of the ongoing Russian-Ukrainian war, which has caused the largest migration in Europe since World War II. The paper explores the dynamics of these changes and ways to adapt urban transportation systems to war conditions. The study aims to determine the parameters of urban transport zones with specific disruptions in network link congestion indices during different phases of the full-scale invasion of Ukraine by the Russian Federation. The research methodology is based on analyzing statistical data on population movements, applying traffic flow models, and conducting a systematic analysis of the interaction between various components of urban transport systems. The goal of this study is to establish the relationships between the areas of cities where disruptions in congestion indices were observed during the initial phase of the invasion. The cities studied are Lviv and Kyiv, whose road networks are also described in the article. Polynomial regression models with two independent variables (the congestion index and the number of days from the beginning of each phase) were developed for three predefined time phases, each with distinct features of the armed conflict. The dependent variable is the area of the city experiencing disruptions in the congestion index relative to normal traffic flow conditions. The study concludes that the relationship between changes in the congestion index and the area of the city experiencing deviations is directly proportional. The absolute values of the indicators studied are lower for Lviv’s network than for Kyiv’s.

Re-evaluating Cambaztepe in the Context of its Yamnaya (Pit-Grave) Origin, the Anatolian Trade Network and Possible Early Migrations towards Anatolia in the 3rd Millennium BC

Abstract This study aims to re-evaluate Cambaztepe, located approximately 12 km west of the Silivri district center of İstanbul, where rescue excavations led by the İstanbul Archaeology Museums in 2015 were carried out. Cambaztepe is a burial mound dated to the Early Bronze Age II (EBA II) within Anatolian chronology. It also has a secondary burial context dated to the Iron Age. Although there is no absolute dating, Cambaztepe is currently believed to be the earliest burial mound in Türkiye’s European territory (also known as Eastern Thrace), considering the burial position and the grave goods and/or finds. The excavation team has published only a preliminary report and two papers, of which one was published in a popular magazine. The possible relationship between Cambaztepe and Yamnaya (Pit-Grave), and other related cultures was not examined in the preliminary report. Furthermore, the preliminary report provides inaccurate and misleading suggestions about the way the deceased were placed in the grave and the grave finds. In addition to other evidence, the way the deceased were placed in the grave as a semi-supine position indicates that the Cambaztepe EBA II grave context is related to the Pit-Grave or other cultures with Pit-Grave traditions in the Balkans. However, the grave structure in round shape with a floor of stone slabs and the grave finds, consisting of a beaked jug of inland Western Anatolian origin and a dagger of Anatolian origin, make Cambaztepe different from contemporary burial mounds in the Balkans. The existence of a cremation burial is sufficient to make concrete suggestions in the context of possible early migrations from Europe to Anatolia in the 3rd millennium BC, even though the exact nature of these migrations remains unknown, whether they involved the population movement or transfer of ideas-ideology-beliefs (or a combination of both). Likewise, the Cambaztepe EBA II grave context has a potential to define the mechanism of migration from Anatolia to Europe more precisely. The Cambaztepe EBA II grave context should be placed at the date range 2700–2500 BC, based on the burial practice observed in the Balkans and the grave finds of Anatolian origin.

Reliability and validity of the Tampa Scale for Kinesiophobia in patients with traumatic hand-forearm injuries.

Fear of movement in patients with traumatic hand-arm injuries can negatively affect functional outcomes. Therefore, it is important to evaluate fear of movement in this patient population. The aim of this study was to investigate the validity and reliability of the Tampa Scale for Kinesiophobia in patients with traumatic hand-forearm injuries. Cross-sectional. Hand rehabilitation unit in a university hospital. The study included 170 patients with traumatic hand-arm injuries and a mean age of 37.57 (11.85) years. Tampa Scale for Kinesiophobia, Pain Catastrophizing Scale, Beck Anxiety Inventory and pain severity rating (via Visual Analog Scale) were completed by interview in the first session. In addition, Modified Hand Injury Scoring System was used to determine severity of the injury. Tampa Scale for Kinesiophobia was re-administered 15 days after the first session. Test-retest reliability, internal consistency, and construct validity of the Tampa Scale for Kinesiophobia were evaluated. In addition, exploratory factor analysis was completed using baseline data. Cronbach's alpha for the scale was 0.604, and test-retest reliability was acceptable (ICC = 0.646). Tampa Scale for Kinesiophobia had a significant relationship with Beck Anxiety Inventory (r = 0.269, p < 0.001), Pain Catastrophizing Scale (r = 0.457, p < 0.001) and pain severity at rest (r = 0.168, p = 0.029). Factor analysis estimated the scale represented five subsections in this population. Psychometric properties of the Tampa Scale for Kinesiophobia were acceptable in patients with hand-forearm injuries. However, since our results were weaker than those in the literature, this should be considered when interpreting the results.

Joint extented Kalman filter-based parameter estimation in networked SEIR models with stochastic variability: analysis using COVID-19 daily data from southern India

Graph Laplacian diffusion is utilised to augment the susceptible-infected-removed (SEIR) epidemic model by integrating a weighted network and introducing variability in the transmission rate parameter to simulate population movement across network nodes. Employing the Joint Extended Kalman filter (JEKF), our objective is to derive three critical parameters: the transmission rate (β), recovery rate (γ), and latent period rate (α). The JEKF's iterative approach continuously anticipates and updates the system state based on current parameter estimations, making it adaptable for parameter estimation in dynamic systems. Integration of model predictions with observed data further enhances accuracy. Subsequently, we offer visual insights and demonstrate our methodology through experiments conducted on a simple tree network and a small-world Watts-Strogatz graph. Our ultimate aim is to precisely determine optimal parameter values to formulate effective COVID-19 management plans tailored for South India.

Estimating dispersal rates and locating genetic ancestors with genome-wide genealogies.

Spatial patterns in genetic diversity are shaped by individuals dispersing from their parents and larger-scale population movements. It has long been appreciated that these patterns of movement shape the underlying genealogies along the genome leading to geographic patterns of isolation-by-distance in contemporary population genetic data. However, extracting the enormous amount of information contained in genealogies along recombining sequences has, until recently, not been computationally feasible. Here, we capitalize on important recent advances in genome-wide gene-genealogy reconstruction and develop methods to use thousands of trees to estimate per-generation dispersal rates and to locate the genetic ancestors of a sample back through time. We take a likelihood approach in continuous space using a simple approximate model (branching Brownian motion) as our prior distribution of spatial genealogies. After testing our method with simulations we apply it to Arabidopsis thaliana. We estimate a dispersal rate of roughly 60 km2/generation, slightly higher across latitude than across longitude, potentially reflecting a northward post-glacial expansion. Locating ancestors allows us to visualize major geographic movements, alternative geographic histories, and admixture. Our method highlights the huge amount of information about past dispersal events and population movements contained in genome-wide genealogies.

Ascertainment of community exposure sites to Ross River virus during the 2020 outbreak in Brisbane, Australia.

This study investigated potential Ross River virus (RRV) exposure sites in Greater Brisbane during the Queensland COVID-19 lockdown (January-July 2020). Using RRV notifications, cluster identification techniques, and mobile phone data for movement network analysis, the study examined 993 RRV cases and 9 million movement trajectories from residential RRV cluster areas (hot-spots). The findings revealed that population movement was a key risk factor to RRV incidence within hotspots whereby highly interconnected areas had more RRV cases during lockdown. While environmental conditions within RRV hot-spot were less significant compared to their connectivity, areas with higher vegetation density had fewer RRV cases. The study also noted that individuals from RRV hot-spots spent less time in green areas pre-lockdown than during and after lockdown. The results suggest that population movement significantly influenced the 2020 RRV outbreak. These insights can help adapt current vector control and surveillance protocols to target areas identified in this study.

Population characteristics, seasonal distribution, and suppression potential of introduced Northern Pike in a Great Plains stream

AbstractObjectiveThe objectives of this study were to describe the population dynamics, reproductive characteristics, and movement of Northern Pike Esox lucius in the Niobrara River drainage of Wyoming. This information was used to estimate the necessary level of suppression to meaningfully reduce their abundance and thereby facilitate persistence of native nongame fishes.MethodsIn 2019 and 2020, Northern Pike were sampled to describe population size structure, age structure, growth, and mortality. An additional 42 gravid female Northern Pike were collected across 2020–2023 to determine a length–fecundity relationship. Vulnerability to recruitment overfishing was modeled with a static spawning potential ratio model. Finally, 15 mature fish were implanted with radio transmitters in 2021 and 2022 and tracked for 1 year to determine seasonal dispersal and spawning locations.ResultSampled Niobrara River drainage Northern Pike (n = 213) varied from 127 to 749 mm total length. Estimated ages of fish were between 0 and 8 years, and total annual mortality was estimated at 42% (95% confidence interval = 36–48%) in the presumed absence of fishing mortality. Recruitment was extremely stable, and growth was relatively fast through age 2. Some females matured at age 1, and all females were mature by age 2 and spawned annually. Estimated total fecundity for females between 297 and 914 mm total length varied from 3573 to 154,877 eggs. Most telemetered fish moved little throughout the year, but movements as large as 5.9 river kilometers were observed. Modeling suggests that exploitation of age‐1 and older Northern Pike should exceed 42% and exploitation of age‐2 and older fish should exceed 85% to meaningfully reduce the population's reproductive potential.ConclusionNorthern Pike growth and reproductive potential at older ages may be more limited in small prairie streams than within their native range. Observed annual home range was small, and spawning occurred annually in consistent locations. The necessary intensity of mechanical removal to achieve meaningful suppression in this system will likely require an intensive and ongoing interstate effort.

Jaringan Saraf Tiruan untuk Memprediksi Jumlah Pertumbuhan Penduduk di Dinas Kependudukan dan Pencatatan Sipil Kabupate Sumba Barat Daya

The purpose of this research is to create a JST (artificial neural network) model that can forecast population growth at the Population and Civil Registration Office of West Sumba Regency. population growth at the Population and Civil Registration Office of West Sumba Regency. Regency. Regional development planning must consider the increasing number of population, therefore proper forecasting is essential to encourage sustainable policies and initiatives. sustainable policies and initiatives. Because it can identify complex patterns in past data and produce more accurate forecasts than traditional techniques, an ANN model is used. traditional techniques, the ANN model is used. The data used in this study is the population growth of Southwest Sumba Regency over the past including characteristics such as birth and death rates and population movements. deaths and population movements. The backpropagation algorithm is used to optimize the multilayer perceptron (MLP) architecture for ANN training. Separating the data into training and testing sets and assessing the models model using metrics such as Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) based on the error. Error (RMSE) based on the prediction error are the steps involved in the training process. involved in the training process. The research findings show that, with a low level of error, the artificial neural network model can estimate the population increase in Southwest Sumba Regency with a reasonable level of accuracy. reasonable level of accuracy. The model is expected to serve as a reference for relevant authorities to better manage population data and as a tool to create more focused and successful population policies.