Effectiveness of the population health and environment approach in improving family planning outcomes in the Gurage, Zone South Ethiopia.

BACKGROUND: Family planning is a strategy of balancing population growth with economic development for sustainable use of natural resources. A high population growth induces increased demand for resources and the rate at which these resources are exploited. Population, health and environment are connected inextricably. Population growth unbalanced with economic development leads to food insecurity which exposes households to the consumption of food with reduced quality and quantity leading to increased risk of malnutrition and poor health. Food insecurity again obliges people to encroach into the natural environment leading to a spiraling progress to destitution. A study in the Philippines provided concrete evidence that integrated development programming incorporating population, health, and the environment (PHE) can be more effective in lowering population growth rates and preserving critical coastal ecosystems than single-sector development interventions". Although the PHE approach has been implemented for 5 years (2008-2012) Guraghe Zone of South Ethiopia, its outcomes have not been evaluated. The objective of this study was to evaluate the effectiveness of PHE approach for achieving family planning (FP) outcomes in Gurage Zone. METHODS: A comparative cross-sectional study was conducted in October, 2012. A total of 962 married women in the reproductive age group were included in the study. Data were collected using an interviewer administered Amharic version questionnaire. Descriptive statistics and multivariable logistic regression analyses were performed to compare the PHE and non-PHE Woredas (district) based on family planning parameters adopted from Measure Evaluation Manual. RESULTS: Comparison of non-new family panning acceptor women showed that PHE Woreda had a significantly high CPR compared to non-PHE (78% vs 52%, P < 0.0001). Among these sub-groups, women in the PHE Woreda were over four times more likely to use family planning methods during the study period (P < 0.0001) compared with women in the non-PHE Woreda. Women whose husbands' supported their use of family planning methods were 17 times as likely to use family panning methods (AOR: 17.2, 95 % CI [11.1, 26.8]), P < 0.0001. This was even increased to 20 times more when we did sub-group analysis only for women who were not new acceptors (AOR: 20.4:95% CI [9.7, 42.7]), P < 0.0001. The qualitative results showed that there was a better integration of FP, health and environmental issues into the grassroots level interventions in the PHE Woreda through using students as a medium for reaching parents on family planning and environmental issues. CONCLUSIONS: The findings suggest that overall; PHE has positive outcomes in FP behaviors both among married women and their husbands. Integration of population, health and environmental issues need to be strengthened and scaled up to sustain the positive FP behaviors such as support of FP use. Strategies used in the PHE Woredas such as using schools and students as medium for integrated PHE interventions are commendable approaches that need to be strengthened.

Geographically skewed recruitment and COVID-19 seroprevalence estimates: a cross-sectional serosurveillance study and mathematical modelling analysis.

OBJECTIVES: Convenience sampling is an imperfect but important tool for seroprevalence studies. For COVID-19, local geographic variation in cases or vaccination can confound studies that rely on the geographically skewed recruitment inherent to convenience sampling. The objectives of this study were: (1) quantifying how geographically skewed recruitment influences SARS-CoV-2 seroprevalence estimates obtained via convenience sampling and (2) developing new methods that employ Global Positioning System (GPS)-derived foot traffic data to measure and minimise bias and uncertainty due to geographically skewed recruitment. DESIGN: We used data from a local convenience-sampled seroprevalence study to map the geographic distribution of study participants' reported home locations and compared this to the geographic distribution of reported COVID-19 cases across the study catchment area. Using a numerical simulation, we quantified bias and uncertainty in SARS-CoV-2 seroprevalence estimates obtained using different geographically skewed recruitment scenarios. We employed GPS-derived foot traffic data to estimate the geographic distribution of participants for different recruitment locations and used this data to identify recruitment locations that minimise bias and uncertainty in resulting seroprevalence estimates. RESULTS: The geographic distribution of participants in convenience-sampled seroprevalence surveys can be strongly skewed towards individuals living near the study recruitment location. Uncertainty in seroprevalence estimates increased when neighbourhoods with higher disease burden or larger populations were undersampled. Failure to account for undersampling or oversampling across neighbourhoods also resulted in biased seroprevalence estimates. GPS-derived foot traffic data correlated with the geographic distribution of serosurveillance study participants. CONCLUSIONS: Local geographic variation in seropositivity is an important concern in SARS-CoV-2 serosurveillance studies that rely on geographically skewed recruitment strategies. Using GPS-derived foot traffic data to select recruitment sites and recording participants' home locations can improve study design and interpretation.

Recruitment location influences bias and uncertainty in SARS-CoV-2 seroprevalence estimates.

The initial phase of the COVID-19 pandemic in the US was marked by limited diagnostic testing, resulting in the need for seroprevalence studies to estimate cumulative incidence and define epidemic dynamics. In lieu of systematic representational surveillance, venue-based sampling was often used to rapidly estimate a community's seroprevalence. However, biases and uncertainty due to site selection and use of convenience samples are poorly understood. Using data from a SARS-CoV-2 serosurveillance study we performed in Somerville, Massachusetts, we found that the uncertainty in seroprevalence estimates depends on how well sampling intensity matches the known or expected geographic distribution of seropositive individuals in the study area. We use GPS-estimated foot traffic to measure and account for these sources of bias. Our results demonstrated that study-site selection informed by mobility patterns can markedly improve seroprevalence estimates. Such data should be used in the design and interpretation of venue-based serosurveillance studies.