Mark C Wheldon Mark C Wheldon
Biographic Data
| ID | 9067460 |
|---|---|
| NAME | Mark C Wheldon Mark C Wheldon |
| GIVEN NAMES | Mark C Wheldon Mark C |
| FAMILY NAME | Wheldon |
| SIGNATURE | WHELDON M C W M C |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 0 |
| EDITOR COUNT | 2 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Cofactors of earlier uptake of modern postpartum family planning methods in Kenya
There are limited data on uptake of postpartum family planning (FP), particularly in high HIV prevalence settings. We assessed the timing of modern postpartum FP initiation and the cofactors of earlier uptake using longitudinal data from a clinical trial conducted in Kenya to assess two models of PrEP delivery among pregnant and postpartum women (NCT#03070600). Time to uptake of modern postpartum FP was estimated using survival analysis methods, …
Tackling public health data gaps through Bayesian high-resolution population estimation
Most low- and middle-income countries face significant public health challenges, exacerbated by the lack of reliable demographic data supporting effective planning and intervention. In such data-scarce settings, statistical models combining geolocated survey data with geospatial datasets enable the estimation of population counts at high spatial resolution in the absence of dependable demographic data sources. This study introduces a Bayesian mod…
No prominent works on this page.
Cofactors of earlier uptake of modern postpartum family planning methods in Kenya
There are limited data on uptake of postpartum family planning (FP), particularly in high HIV prevalence settings. We assessed the timing of modern postpartum FP initiation and the cofactors of earlier uptake using longitudinal data from a clinical trial conducted in Kenya to assess two models of PrEP delivery among pregnant and postpartum women (NCT#03070600). Time to uptake of modern postpartum FP was estimated using survival analysis methods, …
Tackling public health data gaps through Bayesian high-resolution population estimation
Most low- and middle-income countries face significant public health challenges, exacerbated by the lack of reliable demographic data supporting effective planning and intervention. In such data-scarce settings, statistical models combining geolocated survey data with geospatial datasets enable the estimation of population counts at high spatial resolution in the absence of dependable demographic data sources. This study introduces a Bayesian mod…
Environmental health (2 works) · Medicine (2 works) · Population (2 works) · Adolescent Sexual and Reproductive Health (1 works) · Bayesian probability (1 works) · Cartography (1 works) · COVID-19 epidemiological studies (1 works) · Data-Driven Disease Surveillance (1 works) · Economics (1 works) · Estimation (1 works)