{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T06:44:04Z","timestamp":1743144244560,"version":"3.40.3"},"publisher-location":"Cham","reference-count":37,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031579622"},{"type":"electronic","value":"9783031579639"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-57963-9_2","type":"book-chapter","created":{"date-parts":[[2024,4,23]],"date-time":"2024-04-23T07:02:12Z","timestamp":1713855732000},"page":"13-27","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep Learning and\u00a0MCMC with\u00a0aggVAE for\u00a0Shifting Administrative Boundaries: Mapping Malaria Prevalence in\u00a0Kenya"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8271-2575","authenticated-orcid":false,"given":"Elizaveta","family":"Semenova","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8759-5902","authenticated-orcid":false,"given":"Swapnil","family":"Mishra","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0891-4611","authenticated-orcid":false,"given":"Samir","family":"Bhatt","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2477-4217","authenticated-orcid":false,"given":"Seth","family":"Flaxman","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9120-4003","authenticated-orcid":false,"given":"H Juliette T","family":"Unwin","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,4,24]]},"reference":[{"issue":"7","key":"2_CR1","doi-asserted-by":"publisher","first-page":"741","DOI":"10.1002\/(SICI)1097-0258(19970415)16:7<741::AID-SIM501>3.0.CO;2-1","volume":"16","author":"L Bernadinelli","year":"1997","unstructured":"Bernadinelli, L., Pascutto, C., Best, N.G., Gilks, W.R.: Disease mapping with errors in covariates. Stat. Med. 16(7), 741\u2013752 (1997)","journal-title":"Stat. Med."},{"issue":"8","key":"2_CR2","doi-asserted-by":"publisher","first-page":"983","DOI":"10.1002\/sim.4780110802","volume":"11","author":"L Bernardinelli","year":"1992","unstructured":"Bernardinelli, L., Montomoli, C.: Empirical Bayes versus fully Bayesian analysis of geographical variation in disease risk. Stat. Med. 11(8), 983\u20131007 (1992)","journal-title":"Stat. Med."},{"issue":"2","key":"2_CR3","doi-asserted-by":"publisher","first-page":"192","DOI":"10.1111\/j.2517-6161.1974.tb00999.x","volume":"36","author":"J Besag","year":"1974","unstructured":"Besag, J.: Spatial interaction and the statistical analysis of lattice systems. J. Roy. Stat. Soc.: Ser. B (Methodol.) 36(2), 192\u2013225 (1974)","journal-title":"J. Roy. Stat. Soc.: Ser. B (Methodol.)"},{"key":"2_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/BF00116466","volume":"43","author":"J Besag","year":"1991","unstructured":"Besag, J., York, J., Molli\u00e9, A.: Bayesian image restoration, with two applications in spatial statistics. Ann. Inst. Stat. Math. 43, 1\u201320 (1991)","journal-title":"Ann. Inst. Stat. Math."},{"issue":"7572","key":"2_CR5","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1038\/nature15535","volume":"526","author":"S Bhatt","year":"2015","unstructured":"Bhatt, S., et al.: The effect of malaria control on Plasmodium falciparum in Africa between 2000 and 2015. Nature 526(7572), 207\u2013211 (2015)","journal-title":"Nature"},{"issue":"134","key":"2_CR6","doi-asserted-by":"publisher","first-page":"20170520","DOI":"10.1098\/rsif.2017.0520","volume":"14","author":"S Bhatt","year":"2017","unstructured":"Bhatt, S., Cameron, E., Flaxman, S.R., Weiss, D.J., Smith, D.L., Gething, P.W.: Improved prediction accuracy for disease risk mapping using gaussian process stacked generalization. J. Roy. Soc. Interface 14(134), 20170520 (2017)","journal-title":"J. Roy. Soc. Interface"},{"key":"2_CR7","unstructured":"Bingham, E., et al.: Pyro: deep universal probabilistic programming. J. Mach. Learn. Res. 20, 28:1\u201328:6 (2019). http:\/\/jmlr.org\/papers\/v20\/18-403.html"},{"key":"2_CR8","unstructured":"Bradbury, J., et al.: JAX: composable transformations of Python+NumPy programs (2018). http:\/\/github.com\/google\/jax"},{"key":"2_CR9","doi-asserted-by":"crossref","unstructured":"Clayton, D.G.: Bayesian methods for mapping disease risk. In: Geographical and Environmental Epidemiology: Methods for Small-Area Studies, pp. 205\u2013220 (1992)","DOI":"10.1093\/acprof:oso\/9780192622358.003.0018"},{"issue":"6","key":"2_CR10","doi-asserted-by":"publisher","first-page":"1193","DOI":"10.1093\/ije\/22.6.1193","volume":"22","author":"DG Clayton","year":"1993","unstructured":"Clayton, D.G., Bernardinelli, L., Montomoli, C.: Spatial correlation in ecological analysis. Int. J. Epidemiol. 22(6), 1193\u20131202 (1993)","journal-title":"Int. J. Epidemiol."},{"key":"2_CR11","volume-title":"Statistics for Spatial Data","author":"N Cressie","year":"2015","unstructured":"Cressie, N.: Statistics for Spatial Data. Wiley, Hoboken (2015)"},{"key":"2_CR12","doi-asserted-by":"crossref","unstructured":"Gelman, A., Carlin, J.B., Stern, H.S., Rubin, D.B.: Bayesian Data Analysis. Chapman and Hall\/CRC (1995)","DOI":"10.1201\/9780429258411"},{"issue":"7","key":"2_CR13","doi-asserted-by":"publisher","first-page":"1032","DOI":"10.1111\/j.1365-3156.2006.01640.x","volume":"11","author":"A Gemperli","year":"2006","unstructured":"Gemperli, A., et al.: Mapping malaria transmission in West and Central Africa. Trop. Med. Int. Health 11(7), 1032\u20131046 (2006)","journal-title":"Trop. Med. Int. Health"},{"issue":"1","key":"2_CR14","doi-asserted-by":"publisher","first-page":"127","DOI":"10.4081\/gh.2006.287","volume":"1","author":"L Gosoniu","year":"2006","unstructured":"Gosoniu, L., Vounatsou, P., Sogoba, N., Smith, T.: Bayesian modelling of geostatistical malaria risk data. Geospat. Health 1(1), 127\u2013139 (2006)","journal-title":"Geospat. Health"},{"issue":"3","key":"2_CR15","doi-asserted-by":"publisher","first-page":"510","DOI":"10.1177\/1065912916653476","volume":"69","author":"M Hassan","year":"2016","unstructured":"Hassan, M.: A state of change: district creation in Kenya after the beginning of multi-party elections. Polit. Res. Q. 69(3), 510\u2013521 (2016)","journal-title":"Polit. Res. Q."},{"issue":"3","key":"2_CR16","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.1000048","volume":"6","author":"SI Hay","year":"2009","unstructured":"Hay, S.I., et al.: A world malaria map: plasmodium falciparum endemicity in 2007. PLoS Med. 6(3), e1000048 (2009)","journal-title":"PLoS Med."},{"issue":"24","key":"2_CR17","doi-asserted-by":"publisher","first-page":"4871","DOI":"10.1002\/sim.8339","volume":"38","author":"O Johnson","year":"2019","unstructured":"Johnson, O., Diggle, P., Giorgi, E.: A spatially discrete approximation to log-Gaussian Cox processes for modelling aggregated disease count data. Stat. Med. 38(24), 4871\u20134887 (2019)","journal-title":"Stat. Med."},{"issue":"2","key":"2_CR18","doi-asserted-by":"publisher","first-page":"190","DOI":"10.4081\/gh.2016.428","volume":"11","author":"SY Kang","year":"2016","unstructured":"Kang, S.Y., Cramb, S.M., White, N.M., Ball, S.J., Mengersen, K.L.: Making the most of spatial information in health: a tutorial in Bayesian disease mapping for areal data. Geospat. Health 11(2), 190\u2013198 (2016)","journal-title":"Geospat. Health"},{"key":"2_CR19","unstructured":"Kingma, D.P., Welling, M.: Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114 (2013)"},{"key":"2_CR20","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1007\/978-1-4612-1284-3_4","volume-title":"Statistical Models in Epidemiology, the Environment, and Clinical Trials","author":"BG Leroux","year":"2000","unstructured":"Leroux, B.G., Lei, X., Breslow, N.: Estimation of disease rates in small areas: a new mixed model for spatial dependence. In: Halloran, M.E., Berry, D. (eds.) Statistical Models in Epidemiology, the Environment, and Clinical Trials. IMA, vol. 116, pp. 179\u2013191. Springer, New York (2000). https:\/\/doi.org\/10.1007\/978-1-4612-1284-3_4"},{"key":"2_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.spasta.2022.100593","volume":"50","author":"YC MacNab","year":"2022","unstructured":"MacNab, Y.C.: Bayesian disease mapping: past, present, and future. Spatial Stat. 50, 100593 (2022)","journal-title":"Spatial Stat."},{"key":"2_CR22","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1016\/j.csda.2013.04.014","volume":"67","author":"TG Martins","year":"2013","unstructured":"Martins, T.G., Simpson, D., Lindgren, F., Rue, H.: Bayesian computing with INLA: new features. Comput. Stat. Data Anal. 67, 68\u201383 (2013)","journal-title":"Comput. Stat. Data Anal."},{"key":"2_CR23","unstructured":"Mishra, S., Flaxman, S., Berah, T., Pakkanen, M., Zhu, H., Bhatt, S.: $$pi$$VAE: encoding stochastic process priors with variational autoencoders. Stat. Comput. (2022)"},{"key":"2_CR24","unstructured":"Phan, D., Pradhan, N., Jankowiak, M.: Composable effects for flexible and accelerated probabilistic programming in NumPyro. arXiv preprint arXiv:1912.11554 (2019)"},{"issue":"4","key":"2_CR25","doi-asserted-by":"publisher","first-page":"861","DOI":"10.4269\/ajtmh.2010.10-0154","volume":"83","author":"H Reid","year":"2010","unstructured":"Reid, H., et al.: Mapping malaria risk in Bangladesh using Bayesian geostatistical models. Am. J. Trop. Med. Hyg. 83(4), 861 (2010)","journal-title":"Am. J. Trop. Med. Hyg."},{"issue":"4","key":"2_CR26","doi-asserted-by":"publisher","first-page":"1145","DOI":"10.1177\/0962280216660421","volume":"25","author":"A Riebler","year":"2016","unstructured":"Riebler, A., S\u00f8rbye, S.H., Simpson, D., Rue, H.: An intuitive Bayesian spatial model for disease mapping that accounts for scaling. Stat. Methods Med. Res. 25(4), 1145\u20131165 (2016)","journal-title":"Stat. Methods Med. Res."},{"key":"2_CR27","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-4145-2","volume-title":"Monte Carlo Statistical Methods","author":"CP Robert","year":"1999","unstructured":"Robert, C.P., Casella, G., Casella, G.: Monte Carlo Statistical Methods, vol. 2. Springer, New York (1999). https:\/\/doi.org\/10.1007\/978-1-4757-4145-2"},{"issue":"191","key":"2_CR28","doi-asserted-by":"publisher","first-page":"20220094","DOI":"10.1098\/rsif.2022.0094","volume":"19","author":"E Semenova","year":"2022","unstructured":"Semenova, E., et al.: PriorVAE: encoding spatial priors with variational autoencoders for small-area estimation. J. R. Soc. Interface 19(191), 20220094 (2022)","journal-title":"J. R. Soc. Interface"},{"key":"2_CR29","unstructured":"Semenova, E., Verma, P., Cairney-Leeming, M., Solin, A., Bhatt, S., Flaxman, S.: PriorCVAE: scalable MCMC parameter inference with Bayesian deep generative modelling. arXiv preprint arXiv:2304.04307 (2023)"},{"issue":"7677","key":"2_CR30","doi-asserted-by":"publisher","first-page":"515","DOI":"10.1038\/nature24059","volume":"550","author":"RW Snow","year":"2017","unstructured":"Snow, R.W., et al.: The prevalence of Plasmodium falciparum in sub-Saharan Africa since 1900. Nature 550(7677), 515\u2013518 (2017)","journal-title":"Nature"},{"key":"2_CR31","unstructured":"Tanaka, Y., et al.: Spatially aggregated gaussian processes with multivariate areal outputs. In: Advances in Neural Information Processing Systems, vol. 32 (2019)"},{"key":"2_CR32","unstructured":"U.S. President\u2019s Malaria Initiative. U.S. president\u2019s malaria initiative Kenya malaria operational plan FY 2022 (2022). www.pmi.gov"},{"issue":"2","key":"2_CR33","doi-asserted-by":"publisher","first-page":"667","DOI":"10.1214\/20-BA1221","volume":"16","author":"A Vehtari","year":"2021","unstructured":"Vehtari, A., Gelman, A., Simpson, D., Carpenter, B., B\u00fcrkner, P.-C.: Rank-normalization, folding, and localization: an improved R for assessing convergence of MCMC (with discussion). Bayesian Anal. 16(2), 667\u2013718 (2021)","journal-title":"Bayesian Anal."},{"key":"2_CR34","doi-asserted-by":"crossref","unstructured":"Wakefield, J.C., Best, N.G., Waller, L.: Bayesian approaches to disease mapping. In: Spatial Epidemiology: Methods and Applications, vol. 59 (2000)","DOI":"10.1093\/acprof:oso\/9780198515326.003.0007"},{"issue":"10195","key":"2_CR35","doi-asserted-by":"publisher","first-page":"322","DOI":"10.1016\/S0140-6736(19)31097-9","volume":"394","author":"DJ Weiss","year":"2019","unstructured":"Weiss, D.J., et al.: Mapping the global prevalence, incidence, and mortality of Plasmodium falciparum, 2000\u201317: a spatial and temporal modelling study. The Lancet 394(10195), 322\u2013331 (2019)","journal-title":"The Lancet"},{"key":"2_CR36","unstructured":"Yousefi, F., Smith, M.T., Alvarez, M.: Multi-task learning for aggregated data using Gaussian processes. In: Advances in Neural Information Processing Systems, vol. 32 (2019)"},{"key":"2_CR37","unstructured":"Zhu, H., et al.: Aggregated Gaussian processes with multiresolution earth observation covariates. arXiv preprint arXiv:2105.01460 (2021)"}],"container-title":["Lecture Notes in Computer Science","Epistemic Uncertainty in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-57963-9_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,23]],"date-time":"2024-04-23T07:02:51Z","timestamp":1713855771000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-57963-9_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031579622","9783031579639"],"references-count":37,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-57963-9_2","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"24 April 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"Data containing administrative boundaries of Kenya are publicly available: current boundaries () and old boundaries () can be freely downloaded. Malaria prevalence data was obtained from DHS 2015 survey and contains information on locations of clusters and test positivity to calculate district-specific prevalence; it can be requested from the DHS programme (). Code to reproduce the results is available at .","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Data and Code Availability"}},{"value":"Authors do not have any competing interests to declare. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of the National Research Foundation, Singapore","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"Epi UAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Epistemic Uncertainty in Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pittsburgh, PA","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 August 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 August 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"epiuai2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/sites.google.com\/view\/epi-workshop-uai-2023\/home","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}