Accurate Population Estimates Research Articles

The Development and the Assessment of Sampling Methods for Hard-to-Reach Populations in HIV Surveillance.

Due to stigma or legal issues, populations with higher HIV risk are often hard to reach, which impedes accurate population estimation of HIV burden. To better sample hard-to-reach populations (HTRPs) for HIV surveillance, various sampling methods have been designed and/or used since HIV epidemic following the first reported AIDS cases in 1981. This paper describes the development and the assessment (i.e., validity and reproducibility) of approximately eight sampling methods (e.g., convenience sampling, snowball sampling, time location sampling, and respondent-driven sampling) for HTRPs in HIV surveillance, with a focus on respondent-driven sampling (RDS). Compared to other methods, RDS has been greatly assessed. However, current evidence is still inadequate for RDS to be considered the best option for sampling HTRPs. The field must continue to assess RDS and to develop new sampling approaches or modifications to existing approaches.

The Population of Massive Stars in Active Galactic Nuclei Disks

Gravitational instability in the outskirts of active galactic nuclei (AGN) disks leads to disk fragmentation and formation of ∼300 M ⊙ supermassive stars with potentially long lifetimes. Alternatively, stars can be captured ex situ and grow from gas accretion in the AGN disk. However, the number density distribution throughout the disk is limited by thermal feedback as their luminosities provide the dominant heating source. We derive equilibrium stellar surface density profiles under two limiting contexts: in the case where the stellar lifetimes are prolonged, due to the recycling of hydrogen-rich disk gas, only the fraction of gas converted into heat is removed from the disk accretion flow. Alternatively, if stellar composition recycling is inefficient and stars can evolve off the main sequence, the disk accretion rate is quenched toward smaller radii resembling a classical starburst disk, albeit the effective removal rate depends not only on the stellar lifetime, but also the mass of stellar remnants. For AGNs with central supermassive black hole masses of ∼106–108 M ⊙ accreting at ∼0.1 Eddington efficiency, we estimate a total number of 103–105 massive stars and the rate of stellar mergers to be 10−3 to 1 yr−1. We initiate the detailed study of the interaction between a swarm of massive stars through hydro and N-body simulations to provide better prescriptions of dynamical processes in AGN disks, and to constrain more accurate estimates of the stellar population.

Obtaining accurate population estimates with reduced workload and lower fish mortality in multi-mesh gillnet sampling of a large pre-alpine lake.

The EU Water Framework Directive requires monitoring of the ecological status of lakes, with fish as a relevant class of biotic quality indicator, but monitoring fish populations in large lakes is demanding. This study evaluated use in Lake Constance of a novel multi-mesh gillnet modified to reduce catch numbers. In direct comparison with conventional European Committee for Standardization (CEN) nets we achieved 48% reduction in fish mortality with 38% less labour for tasks directly influenced by fish catch numbers, while maintaining comparable species composition and catch per unit effort. Comparison of mesh sizes indicated no significant reduction in species detection in area-reduced panels of the small mesh sizes, while total observed species richness was greater when using the modified nets. Differences in benthic species communities among depth strata were common, while those of pelagic zones were more homogeneous and did not differ significantly with depth. Catches of different net types from the same depth stratum did not exhibit significant differences. The dominance structure of the most common species, relevant to lake assessment, was similar in catches of both net types, suggesting overall superiority of the modified nets in Lake Constance. Sampling conducted according to standard European CEN protocol, while deploying 60% fewer nets, yielded sufficiently precise abundance estimates for monitoring shallow areas of the benthic zone. A 50% difference in the abundance of dominant species was detected among sampling events with a certainty of 95%. The sample did not provide comparable accuracy in deep benthic strata or the pelagic zone, but was adequate to record complete inventories of species present. Based on this trial data, a new stratified sampling design is proposed for monitoring large lake fish communities for ecological assessment. Depth-dependent fish communities were used to calculate the required number of nets, which resulted in a 69% reduction for the entire lake compared to the CEN calculation method. Using the modified nets increases the feasibility of performing WFD surveys, by reducing effort and cost, while the simultaneous halving of fish mortality minimises the negative impact of fish surveys.

Uncovering extensive populations of the ‘threatened’ Black Crowned Cranes in Gambella, Ethiopia

A reliable assessment of the population size of threatened species is crucial for making informed decisions about their conservation and management. However, there is a lack of comprehensive knowledge on the population of the eastern Black Crowned Crane (Balearica pavonina ceciliae), which is globally recognized as a threatened taxon experiencing a declining population trend. Here, we investigated the density, abundance and factors that influence flock size in the wetlands of the Gambella region in Ethiopia. We used line transects to collect data during dry and wet seasons. Population density and abundance were estimated using DISTANCE software, whereas factors influencing crane flock size were evaluated using a generalized linear model. We found that crane density ranged from 444 to 965 birds per sq km in the dry season and from 62 to 105 individuals per sq km in the wet season. We estimated that the population size within the designated survey areas as 7634 during the dry season and 866 during the wet season. Furthermore, for the broader survey region that encompasses permanent wetlands, the estimated population ranged from 9138 to 19,849 individuals in the dry season and from 1272 to 2166 individuals in the wet season. We found that grazing intensity and proximity to woodlands and rivers had significant positive impacts on crane flock size, whereas an increase in wetland water depth and grass height remarkably reduced flock size. As a result, wetland habitat degradation-related problems are not currently a threat to cranes in this region, but are likely to increase in the future due to large-scale agricultural expansion. The crane population size we estimated in Gambella is high, three to four times higher than the estimate from the entirety of Ethiopia. Our research underscores the global significance of Gambella wetlands as an important habitat for cranes. However, to obtain an accurate population estimate in this region, it is imperative to include seasonal wetlands, savannah grasslands, farmlands and the extended wetlands of South Sudan, which are hydrologically connected to the wetlands of Gambella region. To achieve this, comprehensive surveys and estimations should incorporate various techniques, such as aerial surveys, satellite telemetry, and high-resolution satellite imagery.

Simulation Modeling to Assess Line Transect Distance Sampling Under a Range of Translocation Scenarios

Abstract The accuracy of posttranslocation population monitoring methods is critical to assessing long-term success in translocation programs. Translocation can produce unique challenges to monitoring efforts; therefore, it is important to understand the flexibility and robustness of commonly used monitoring methods. In Florida, USA, thousands of gopher tortoises Gopherus polyphemus have been, and continue to be, translocated from development sites to permitted recipient sites. These recipient sites create a broad range of potential monitoring scenarios due to variability in soft-release strategies, habitat conditions, and population demographics. Line transect distance sampling is an effective method for monitoring natural tortoise populations, but it is currently untested for translocated populations. We therefore produced 3,024 individual-based, spatially explicit scenarios of translocated tortoise populations that differed in recipient site and tortoise population properties, based on real-world examples, literature review, and expert opinion. We virtually sampled simulated tortoise populations by using line transect distance sampling methods and built a Bayesian hierarchical model to estimate the population density for each simulation, which incorporated individual-level covariates (i.e., burrow width and burrow occupancy). Line transect distance sampling was largely appropriate for the conditions that typify gopher tortoise recipient sites, particularly when detection probability on the transect lines was greater than or equal to 0.85. Designing the layout of transects relative to the orientation of soft-release pens, to avoid possible sampling biases that lead to extreme outliers in estimates of tortoise densities, resulted in more accurate population estimates. We also suggest that use of individual-level covariates, applied using a Bayesian framework as demonstrated in our study, may improve the applicability of line transect distance sampling surveys in a variety of contexts and that simulation can be a powerful tool for assessing survey design in complex sampling situations.

A review of field techniques to estimate lion presence and abundance

Abstract Since the 1990s, the number of lions (Panthera leo) has declined by about 43% across African range states. Reliable lion population estimates can contribute to effective management and inform local and international conservation policies. Though many survey methods have been used to estimate lion abundance, an assessment of their usefulness and effectiveness is lacking. We reviewed and identified available methods used to estimate lion populations, then investigated their feasibility, cost‐effectiveness and suitability to achieve primary objectives. We identified 12 methods in two categories: direct (minimum counts, call‐in surveys, capture–recapture, opportunistic sightings, remote cameras, distance‐based and aerial counts) and indirect (track counts, secondary information, prey‐based, genetic samples and roar counts). We identified 48 studies (57%) in which lion population estimation was not repeatable. Additionally, 38% did not provide any measure of precision. About 28% of the studies were conducted specifically for management purposes, while remaining studies focused on population estimates and dynamics. Because data from these studies have influenced local management and global lion conservation policies, we recommend basing future policies and management on repeatable, precise and accurate population estimates supported by appropriate and cost‐effective experimental designs. In most cases, these estimates are obtained through actual lion counts derived from direct observation methods including call‐in, capture–recapture and remote camera surveys or through reliable animal signs such as genetic samples.

Estimating prevalence of early symptomatic Alzheimer's disease in the United States.

Understanding the prevalence of treatment-eligible Alzheimer's disease (AD) is crucial for policy planning. We used a comprehensive literature review and population cascade approach to estimate the number of amyloid-positive, clinically diagnosed patients with mild cognitive impairment (MCI) or mild dementia due to AD in the United States. An estimated 666,646 individuals were identified as having MCI due to AD (range: 351,926-1,227,776) and 620,850 individuals as having mild dementia due to AD (range: 445,082-820,339). In a US population of 76 million individuals aged 60 or older in 2021, the estimates of MCI and mild dementia due to AD increased with age. As earlier diagnosis of AD and new disease-modifying treatments become available, accurate population estimates are required to reduce uncertainty in the number of clinically diagnosed patients eligible for amyloid-targeting therapies.

Integrating Reward Maximization and Population Estimation: Sequential Decision-Making for Internal Revenue Service Audit Selection

We introduce a new setting, optimize-and-estimate structured bandits. Here, a policy must select a batch of arms, each characterized by its own context, that would allow it to both maximize reward and maintain an accurate (ideally unbiased) population estimate of the reward. This setting is inherent to many public and private sector applications and often requires handling delayed feedback, small data, and distribution shifts. We demonstrate its importance on real data from the United States Internal Revenue Service (IRS). The IRS performs yearly audits of the tax base. Two of its most important objectives are to identify suspected misreporting and to estimate the "tax gap" -- the global difference between the amount paid and true amount owed. Based on a unique collaboration with the IRS, we cast these two processes as a unified optimize-and-estimate structured bandit. We analyze optimize-and-estimate approaches to the IRS problem and propose a novel mechanism for unbiased population estimation that achieves rewards comparable to baseline approaches. This approach has the potential to improve audit efficacy, while maintaining policy-relevant estimates of the tax gap. This has important social consequences given that the current tax gap is estimated at nearly half a trillion dollars. We suggest that this problem setting is fertile ground for further research and we highlight its interesting challenges. The results of this and related research are currently being incorporated into the continual improvement of the IRS audit selection methods.

Refining United States Sexual Minority Adult Population Estimates with the Inclusion of "Something Else" and "Don't Know" Survey Responses.

Purpose: To refine estimates of the U.S. sexual minority population, we sought to characterize trends in the odds of respondents selecting "something else" or "don't know" when asked about sexual orientation on the National Health Interview Survey and to reclassify those respondents likely to be sexual minority adults. Methods: Logistic regression was conducted to test whether the odds of selecting "something else" or "don't know" increased over time. A previously established analytic approach was used to identify sexual minority adults among these respondents. Results: Between 2013 and 2018, the percentage of respondents selecting "something else" or "don't know" increased 2.7-fold, from 0.54% to 1.44%. Reclassifying respondents with >50% predicted probabilities of being sexual minorities increased sexual minority population estimates by as much as 20.2%. Conclusion: A growing proportion of adults are selecting "something else" or "don't know." Properly classifying these responses yields more accurate sexual minority population estimates.

Uncovering inbreeding, small populations, and strong genetic isolation in an Australian threatened frog, Litoria littlejohni

AbstractThe status of many amphibian populations remains unclear due to undetected declines driven by disease and difficulties in obtaining accurate population estimates. Here, we used genome complexity reduction-based sequencing technology to study the poorly understood Littlejohn’s treefrog, Litoria littlejohni across its fragmented distribution in eastern Australia. We detected five identifiable genetic clusters, with moderate to strong genetic isolation. At a regional scale, population isolation was likely driven by population crashes, resulting in small populations impacted by founder effects. Moderate genetic isolation was detected among populations on the Woronora Plateau despite short distances between population clusters. Evidence of recent declines was apparent in three populations that had very small effective population size, reduced genetic diversity and high inbreeding values. The rates of inbreeding detected in these populations combined with their small size leave these populations at elevated risk of extinction. The Cordeaux Cluster was identified as the most robust population as it was the largest and most genetically diverse. This study exemplifies the value of employing genetic methods to study rare, cryptic species. Despite low recapture rates using traditional capture-recapture demographic methods, we were able to derive population estimates, describe patterns of gene flow, and demonstrate the need for urgent conservation management.

Exploring the Correlations Between SNPP-VIIRS Nighttime Light Data and Population From a Multiple Scale Perspective

Remote sensing nighttime light (NTL) data are widely used for fine-grained estimation of population due to their effectiveness in monitoring anthropic lights at night. However, there is a lack of research exploring the correlations between population and NTL data at various administrative and grid scales, as well as their related impact factors. Thus, to analyze the spatial effect of NTL on NTL-based population estimation, five models (linear, quadratic, exponential, logarithmic, and power function) were used in this letter to examine the correlations between NTL and population at multiscale by using the Visible Infrared Imaging Radiometer Suite data from the National Polar-orbiting Partnership. Results show that the correlations between NTL and population were significantly related to geographic scales. The power function model had the highest fitting accuracy between NTL and population when the grid scales were less than 5 km. The quadratic model had the highest precision on grid scales larger than 5 km. It showed a sharp increase in R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> values between 0.5 and 10 km as the scale increase. At different scales, the correlations between NTL and population was negatively impacted by temperature, Normalized Difference Vegetation Index (NDVI), and Road Network Density (RND), but they were positively impacted by the Relief Degree of Land Surface (RDLS). We also found that RDLS had the greatest impact on model accuracy, followed by NDVI and temperature. In addition, RND had a low impact on the accuracy of population estimation on rough grids.

Examining the value of satellite data in halting transmission of polio in Nigeria: A socioeconomic analysis

Abstract In 2014, Nigeria halted transmission of wild poliovirus for the first time in its history. A critical enabling component in this historic achievement was the use of satellite data to produce more accurate maps and population estimates used in planning and implementing vaccination campaigns. This article employs a value-of-information approach to estimate the net socioeconomic benefits associated with this use of satellite data. We calculate the increase in the likelihood of halting transmission of polio associated with the use of satellite-based information compared to traditional data sources, and we consider the benefits associated with savings to the healthcare system as well as health benefits. Using a conservative approach focused on just 1 year of benefits, we estimate net socioeconomic benefits of between $46.0 million and $153.9 million. In addition to these quantified benefits, we also recognize qualitative benefits associated with improving human health, reaching marginalized communities, and building capacity among local populations. We also explore the substantial benefits associated with follow-on projects that have made use of the satellite-based data products and methodologies originally developed for the Nigeria polio eradication effort.

Methodological strengths and weakness of cohorts and administrative data for developing population estimates of dementia

AbstractBackgroundThere are three main methods of obtaining population data on the incidence and/or prevalence of dementia: cross‐sectional surveys (which may be repeated over time); cohort studies that follow people initially without dementia and count newly diagnosed cases over time; and administrative health records (including linkage of records from multiple sources). The major challenges for all these methods are: how well the study sample represents the target population, the accuracy of diagnoses, and the costs of maintaining the data collection over time.MethodIn a project to improve Australia’s dementia statistics, we conducted a series of studies to compare population estimates of dementia obtained using different methods. Firstly, we used existing general health studies of community‐based cohorts, supplemented by linkage to administrative records of hospital and emergency department admissions, assessments for aged care support, medication prescriptions, and death certificates to estimate the cumulative incidence of dementia. Secondly, we created cohorts based on administrative records for entire populations. Thirdly, we assessed the validity of the identification of people with dementia in the record linkage cohorts in various ways, including linkage with studies that had obtained clinical diagnosis through the standardised assessment of participants.ResultWe will present empirical results illustrating the strengths and limitations of these different approaches. In summary, community‐based cohort studies lack representativeness of national or regional populations due to recruitment biases and differential loss to follow‐up. Cohort studies are also costly to maintain over the long time needed for participants to develop dementia. In contrast, the use of administrative records is relatively inexpensive, but is subject to policy changes that impact on the continuity of data coverage and quality. Population coverage may also be problematic for administrative data if important sources of care for people with dementia are not included; for example, in Australia linkable primary care data are not available. The validation studies showed that accuracy was highly dependent on data sources, and identification of dementia type was unreliable.ConclusionPrevalence and trends data of dementia obtained from multiple sources are needed to provide accurate population estimates, together with detailed contextual knowledge and careful analysis.

Deadly declines and diversity – understanding the variations in regional Aboriginal and Torres Strait Islander smoking prevalence

Deadly declines and diversity – understanding the variations in regional Aboriginal and Torres Strait Islander smoking prevalence

Development of current estimated household data and agent-based simulation of the future population distribution of households in Japan

In response to the declining population and aging infrastructure in Japan, local governments are implementing compact city policies in the form of location normalization plans. To optimize the reorganization of urban public infrastructure, it is important to provide detailed and accurate forecasts of the distribution of urban populations and households. However, several local governments do not have the necessary data and forecasting capability. Moreover, current forecasts of gender- and age-based population data only exist at the municipal level, and household data are exclusively available by family type at the prefecture level. Meanwhile, the accuracy is limited with an assumption of the same rate of change of population in all municipalities and within each city. Therefore, the aim of this study was to develop an agent-based microsimulation household transition model, with the household as the unit and agent. Household data was estimated for all cities in Japan from 2015. Estimated household data comprised of family type, house type, and address, age, and gender of household members, obtained from the national census, and building data. The resulting household transition model was used to forecast the attributes of each household every five years. Simulations in Toyama and Shizuoka Prefectures, Japan from 1980 to 2010 provided highly accurate estimates of municipal-level population by age and household volume by family type. The proposed model was further applied to predict the future distribution of disappearing villages and vacant houses in Japan.

Optimising Berlese funnel extraction for population estimates of adult Cyrtobagous salviniae from Salvinia molesta

ABSTRACT The invasive floating aquatic macrophyte giant salvinia (Salvinia molesta) can rapidly alter ecosystem stability by forming a thick vegetative mat on the water surface. Management efforts are often required to clear waterways, and field releases of the salvinia weevil (Cyrtobagous salviniae) has been successful in restoring aquatic systems. Measuring weevil densities is critical to determine the success of this agent, thus routine Berlese funnel extractions from salvinia should be conducted. A laboratory study was designed to examine how to optimise adult weevil extraction under realistic salvinia biomasses and light intensities (heat source), and a second lab study was conducted to determine the effect of temperature and relative humidity on adult weevil behaviour. The objectives were to improve recommendations to ensure accurate population estimates in a reasonable period and understand what may drive adult weevil movement. We found that weevil movement from salvinia was initiated by increasing temperature above 40°C and decreasing relative humidity below 40%. For the purpose of expediting management decisions, we suggest completing extractions between 48 and 72 h, which requires biomass to be between 0.3 and 0.6 kg with halogen light bulbs of 60 or 75 watts. Additionally, we discovered that thermal stress to the insect was buffered by relative humidity, with individuals showing signs of stress at 3.5°C less when subjected to low initial humidity (∼55%), relative to high (100%). The change in thermal tolerance under different humidity scenarios may be explained by the weevil being a semi-aquatic insect that requires an aquatic plant host.

Development of an imputation model to recalibrate birth weights measured in the early neonatal period to time at delivery and assessment of its impact on size-for-gestational age and low birthweight prevalence estimates: a secondary analysis of a pregnancy cohort in rural Nepal

ObjectivesIn low-income countries, birth weights for home deliveries are often measured at the nadir when babies may lose up of 10% of their birth weight, biasing estimates of small-for-gestational age...

A Practical Assessment of Using sUASs (Drones) to Detect and Quantify Wright Fishhook Cactus (Sclerocactus wrightiae L.D. Benson) Populations in Desert Grazinglands

Obtaining accurate plant population estimates has been integral in listing, recovery, and delisting species under the U.S. Endangered Species Act of 1973 and for monitoring vegetation in response to livestock grazing. Obtaining accurate population estimates remains a daunting and labor-intensive task. Small unmanned aircraft systems (sUASs or drones) may provide an effective alternative to ground surveys for rare and endangered plants. The objective of our study was to evaluate the efficacy of sUASs (DJI Phantom 4 Pro) for surveying the Wright fishhook cactus (Sclerocactus wrightiae), a small (1–8 cm diameter) endangered species endemic to grazinglands in the southwest desert of Utah, USA. We assessed sUAS-based remotely sensed imagery to detect and count individual cacti compared to ground surveys and estimated optimal altitudes (10 m, 15 m, or 20 m) for collecting imagery. Our results demonstrated that low altitude flights provided the best detection rates (p &lt; 0.001) and counts (p &lt; 0.001) compared to 15 m and 20 m. We suggest that sUASs can effectively locate cactus within grazingland areas, but should be coupled with ground surveys for higher accuracy and reliability. We also acknowledge that these technologies may have limitations in effectively detecting small, low-growing individual plants such as the small and obscure fishhook cactus species.

Optimizing the Use of Semiochemical-Based Traps for Efficient Monitoring of Popillia japonica (Coleoptera: Scarabaeidae): Validation of a Volumetric Approach.

Japanese beetle, Popillia japonica Newman, is an invasive insect, native to Japan. The species was detected in the United States in New Jersey in 1916, and then first confirmed in Minnesota in 1968. Since their arrival, P. japonica has become a major pest in turfgrass and several crop agroecosystems. As P. japonica continues to spread throughout the U.S., it’s important to discover more efficient ways to monitor adult populations. In 2018–2020, due to the high volume of P. japonica beetles collected in traps, a comparison of weight and volume calibration methods was conducted in Minnesota. Each method yielded a strong goodness of fit with counts of beetles captured. However, with a goal of cost-effective use of traps and in-field estimates, the volume-based approach was the preferred, most efficient method. In addition, a comparison of monitoring systems was conducted to observe differences in trap type, lure age, and check interval. Results from these studies indicate a standard green/yellow trap, and multi-component, semiochemical-based lure used for the duration of the P. japonica flight period, and a weekly check interval will minimize sampling time and resources, while providing accurate population estimates. In addition, results from these studies will benefit growers and researchers as they continue to explore integrated pest management (IPM) strategies for P. japonica. More importantly, by reducing the time required to quantify trap catches and rebait traps, these results may also facilitate area-wide tracking of P. japonica populations in newly invaded regions.

Estimating elephant density using motion‐sensitive cameras: challenges, opportunities, and parameters for consideration

AbstractWith extinction rates far exceeding the natural background rate, reliable monitoring of wildlife populations has become crucial for adaptive management and conservation. Robust monitoring is often labor intensive with high economic costs, particularly in the case of those species that are subject to illegal poaching, such as elephants, which require frequent and accurate population estimates over large spatial scales. Dung counting methods are commonly employed to estimate the density of elephants; however, in the absence of a full survey calibration, these can be unreliable in heterogeneous habitats where dung decay rates may be highly variable. We explored whether motion‐sensitive cameras offer a simple, lower cost, and reliable alternative for monitoring in challenging forest environments. We estimated the density of African savanna elephants (Loxodanta africana) in a montane forest using the random encounter model and assessed the importance of surveying parameters for future survey design. We deployed motion‐sensitive cameras in 65 locations in the Aberdare Conservation Area in Kenya during June to August in 2015 to 2017, for a survey effort of 967 days, and a mean encounter rate of 0.09 ± 0.29 (SD) images/day. Elephants were captured in 16 locations. Density estimates varied between vegetation types, with estimates ranging from 6.27/km2 in shrub, 1.1/km2 in forest, 0.53/km2 in bamboo (Yushania alpine), and 0.44/km2 in the moorlands. The average speed of animal movement and the camera detection zone had the strongest linear associations with density estimates (R = −0.97). The random encounter model has the potential to offer an alternative, or complementary method within the active management framework for monitoring elephant populations in forests at a relatively low cost.