×

Modeling the marked presence-only data: a case study of estimating the female sex worker size in Malawi. (English) Zbl 1506.62535

Summary: Certain subpopulations like female sex workers (FSW), men who have sex with men (MSM), and people who inject drugs (PWID) often have higher prevalence of HIV/AIDS and are difficult to map directly due to stigma, discrimination, and criminalization. Fine-scale mapping of those populations contributes to the progress toward reducing the inequalities and ending the AIDS epidemic. In 2016 and 2017, the PLACE surveys were conducted at 3290 venues in 20 out of the total 28 districts in Malawi to estimate the FSW sizes. These venues represent a presence-only dataset where, instead of knowing both where people live and do not live (presence-absence data), only information about visited locations is available. In this study, we develop a Bayesian model for presence-only data and utilize the PLACE data to estimate the FSW size and uncertainty interval at a \(1,5\times 1,5\)-km resolution for all of Malawi. The estimates can also be aggregated to any desirable level (city/district/region) for implementing targeted HIV prevention and treatment programs in FSW communities, which have been successful in lowering the incidence of HIV and other sexually transmitted infections.

MSC:

62P25 Applications of statistics to social sciences
62F15 Bayesian inference

Software:

spBayes; brms; R
PDFBibTeX XMLCite
Full Text: DOI arXiv

References:

[1] Banerjee, S.; Carlin, B. P.; Gelfand, A. E., Hierarchical Modeling and Analysis for Spatial Data (2014), New York: Chapman and Hall/CRC, New York
[2] Bürkner, P.-C., “Brms: An R Package for Bayesian Multilevel Models Using Stan, Journal of Statistical Software, 80, 1 (2017)
[3] Carlin, B. P.; Xia, H.; Devine, O.; Tolbert, P.; Mulholland, J.; Gatsonis, C.; Kass, R. E.; Carlin, B.; Carriquiry, A.; Gelman, A.; Verdinelli, I.; West, M., Case Studies in Bayesian Statistics, 140, Spatio-Temporal Hierarchical Models for Analyzing Atlanta Pediatric Asthma ER Visit Rates, 303-320 (1999), New York: Springer, New York
[4] Gelfand, A. E.; Zhu, L.; Carlin, B. P., “On the Change of Support Problem for Spatio-Temporal Data, Biostatistics, 2, 31-45 (2001) · Zbl 1022.62095
[5] Gelman, A., “Two Simple Examples for Understanding Posterior p-Values Whose Distributions Are Far From Uniform, Electronic Journal of Statistics, 7, 2595-2602 (2013) · Zbl 1294.62049
[6] Joint United Nations Programme on HIV/AIDS, 90-90-90: An Ambitious Treatment Target to Help End the Aids Epidemic (2014), Geneva: UNAIDS, Geneva
[7] Joint United Nations Programme on HIV/AIDS, The Gap Report (2014), Geneva, Switzerland: Joint United Nations Programme on HIV/AIDS, Geneva, Switzerland
[8] Joint United Nations Programme on HIV/AIDS, UNAIDS Data 2018 (2018), Geneva, Switzerland: UNAIDS, Geneva, Switzerland
[9] Joint United Nations Programme on HIV/AIDS, End Inequalities. End Aids. Global Aids Strategy 2021-2026 (2021), Geneva: UNAIDS, Geneva
[10] Kerrigan, D.; Kennedy, C. E.; Morgan-Thomas, R.; Reza-Paul, S.; Mwangi, P.; Win, K. T.; McFall, A.; Fonner, V. A.; Butler, J., “A Community Empowerment Approach to the HIV Response Among Sex Workers: Effectiveness, Challenges, and Considerations for Implementation and Scale-up, The Lancet, 385, 172-185 (2015)
[11] Lambert, D., “Zero-Inflated Poisson Regression, With an Application to Defects in Manufacturing, Technometrics, 34, 1-14 (1992) · Zbl 0850.62756
[12] Measure Evaluation (2018)
[13] Meng, X.-L., “Posterior Predictive p-Values, The Annals of Statistics, 22, 1142-1160 (1994) · Zbl 0820.62027
[14] Mugglin, A. S.; Carlin, B. P.; Gelfand, A. E., “Fully Model-Based Approaches for Spatially Misaligned Data, Journal of the American Statistical Association, 95, 877-887 (2000)
[15] Noaa, “Version 1 Viirs Day/Night Band Nighttime Lights.” (2016)
[16] Nychka, D.; Furrer, R.; Paige, J.; Sain, S., Fields: Tools for Spatial Data (2017), Boulder, CO, USA: University Corporation for Atmospheric Research, Boulder, CO, USA
[17] Pearce, J. L.; Boyce, M. S., “Modelling Distribution and Abundance With Presence-Only Data, Journal of Applied Ecology, 43, 405-412 (2006)
[18] Phillips, S. J.; Anderson, R. P.; Schapire, R. E., “Maximum Entropy Modeling of Species Geographic Distributions, Ecological modelling, 190, 231-259 (2006)
[19] Phillips, S. J.; Dudík, M.; Schapire, R. E., A Maximum Entropy Approach to Species Distribution Modeling, 83 (2004)
[20] Puig, P.; Valero, J., “Characterization of Count Data Distributions Involving Additivity and Binomial Subsampling, Bernoulli, 13, 544-555 (2007) · Zbl 1127.62009
[21] Core Team, R., R: A Language and Environment for Statistical Computing (2019), Vienna, Austria: R Foundation for Statistical Computing, Vienna, Austria
[22] Renner, I. W.; Elith, J.; Baddeley, A.; Fithian, W.; Hastie, T.; Phillips, S. J.; Popovic, G.; Warton, D. I., “Point Process Models for Presence-Only Analysis, Methods in Ecology and Evolution, 6, 366-379 (2015)
[23] Riutort-Mayol, G., Bürkner, P.-C., Andersen, M. R., Solin, A., and Vehtari, A. (2020), “Practical Hilbert Space Approximate Bayesian Gaussian Processes for Probabilistic Programming,” arXiv:2004.11408.
[24] Stan Development Team (2020)
[25] UNC, CEDEP, NAC, and FHI360. (2018), Place Report Malawi: September 2018.
[26] Ward, G.; Hastie, T.; Barry, S.; Elith, J.; Leathwick, J. R., “Presence-Only Data and the EM Algorithm, Biometrics, 65, 554-563 (2009) · Zbl 1167.62098
[27] WorldPop, “Malawi 100m Population.” (2015)
[28] Young, L. J.; Gotway, C. A.; Yang, J.; Kearney, G.; DuClos, C., “Linking Health and Environmental Data in Geographical Analysis: It’s So Much More Than Centroids, Spatial and Spatio-Temporal Epidemiology, 1, 73-84 (2009)
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.