Factors influencing fever care-seeking for children under five years of age in The Gambia: a secondary analysis of 2019-20 DHS data.

Background: Malaria contributes to excess child mortality in The Gambia. Children under five are at risk of severe malaria and death if not treated promptly and appropriately. It is crucial that a child with fever receive appropriate care from a trained provider.

Representative Public Health Surveys Pose Several Challenges: Lessons Learned Across 9 Communities During the COVID-19 Pandemic.

Community surveillance surveys offer an opportunity to obtain important and timely public health information that may help local municipalities guide their response to public health threats. The objective of this paper is to present approaches, challenges, and solutions from SARS-CoV-2 surveillance surveys conducted in different settings by 2 research teams. For rapid assessment of a representative sample, a 2-stage cluster sampling design was developed by an interdisciplinary team of researchers at Oregon State University between April 2020 and June 2021 across 6 Oregon communities.

Hidden population size estimation and diagnostics using two respondent-driven samples with applications in Armenia.

Estimating the size of hidden populations is essential to understand the magnitude of social and healthcare needs, risk behaviors, and disease burden. However, due to the hidden nature of these populations, they are difficult to survey, and there are no gold standard size estimation methods. Many different methods and variations exist, and diagnostic tools are needed to help researchers assess method-specific assumptions as well as compare between methods.

Evaluation of a Wastewater-Based Epidemiological Approach to Estimate the Prevalence of SARS-CoV-2 Infections and the Detection of Viral Variants in Disparate Oregon Communities at City and Neighborhood Scales.

Background: Positive correlations have been reported between wastewater SARS-CoV-2 concentrations and a community's burden of infection, disease or both. However, previous studies mostly compared wastewater to clinical case counts or nonrepresentative convenience samples, limiting their quantitative potential.

Objectives: This study examined whether wastewater SARS-CoV-2 concentrations could provide better estimations for SARS-CoV-2 community prevalence than reported cases of COVID-19.

Populations size estimations using SS-PSE among MSM in four European cities: how many MSM are living with HIV?

Background: Although men who have sex with men (MSM) are considered at high risk for transmission of sexually transmitted infections, including HIV, there are few studies estimating the population size of MSM in Europe. We used network data from a survey of MSM in four cities to perform successive sampling-population size estimations (SS-PSE) to estimate MSM population sizes.

Methods: Data were collected in 2013-14 in Bratislava, Bucharest, Verona and Vilnius using respondent-driven sampling (RDS).

Linking subsistence harvest diversity and productivity to adaptive capacity in an Alaskan food sharing network.

Background: Although anthropogenic climate change poses existential challenges for Indigenous communities in the Arctic, these challenges are not entirely unprecedented. Over many generations, Arctic peoples have developed a wide range of behavioral strategies to navigate environmental change and uncertainty, and these strategies provide a foundation for contemporary adaptation.

Aims: In this article, we focus on mixed cash-subsistence economies and the social networks that underlie them in Alaska.

Population Size Estimations Among Hidden Populations Using Respondent-Driven Sampling Surveys: Case Studies From Armenia.

Background: Estimates of the sizes of hidden populations, including female sex workers (FSW), men who have sex with men (MSM), and people who inject drugs (PWID), are essential for understanding the magnitude of vulnerabilities, health care needs, risk behaviors, and HIV and other infections.

Objective: This article advances the successive sampling-population size estimation (SS-PSE) method by examining the performance of a modification allowing visibility to be jointly modeled with population size in the context of 15 datasets. Datasets are from respondent-driven sampling (RDS) surveys of FSW, MSM, and PWID from three cities in Armenia.

Measuring a hidden population: A novel technique to estimate the population size of women with sexual violence-related pregnancies in South Kivu Province, Democratic Republic of Congo.

Successive sampling (SS)-population size estimation (PSE) is a technique used to estimate the sizes of hidden populations using data collected in respondent-driven sampling (RDS) surveys. We assess past estimations and use new data from an RDS survey to calculate a new PSE. In 2012, 852 adult women in South Kivu Province, Democratic Republic of Congo, who self-identified as survivors of sexual violence, resulting in a pregnancy, since the start of the war (in 1996) were sampled using RDS.

Estimating the Size of Hidden Populations Using Respondent-driven Sampling Data: Case Examples from Morocco.

Background: Respondent-driven sampling is used worldwide to estimate the population prevalence of characteristics, such as HIV/AIDS and associated risk factors in hard-to-reach populations. Estimating the total size of these populations is of great interest to national and international organizations; however, reliable measures of population size often do not exist.

Methods: Successive sampling-population size estimation (SS-PSE) along with network size imputation allows population size estimates to be made without relying on separate studies or additional data (as in network scale-up, multiplier, and capture-recapture methods), which may be biased.

Assaying organochlorines in archived serum for a large, long-term cohort: implications of combining assay results from multiple laboratories over time.

Conserving irreplaceable, archived serum samples may sometimes conflict with the objective of minimizing measurement error due to laboratory effects. We sought to determine whether we could successfully combine assay results for DDT-related compounds and polychlorinated biphenyls (PCBs) in serum from the same birth cohort obtained from different laboratories over time. Using the Child Health and Development Studies (CHDS) serum archive, we compared variability for assays of a quality control pool to variability for assays of subject serum.