2014
A space-time point process model for analyzing and predicting case patterns of diarrheal disease in northwestern Ecuador
Ahn J, Johnson T, Bhavnani D, Eisenberg J, Mukherjee B. A space-time point process model for analyzing and predicting case patterns of diarrheal disease in northwestern Ecuador. Spatial And Spatio-temporal Epidemiology 2014, 9: 23-35. PMID: 24889991, PMCID: PMC4044631, DOI: 10.1016/j.sste.2014.02.001.Peer-Reviewed Original ResearchConceptsSampled communitiesNorthwestern EcuadorLog Gaussian Cox processRiver BasinRisk-related parametersTemporal variationSpace-time modelDiarrheal diseaseLongitudinal sampling designSampling designPoint process modelNatural environmentSampling regionSpatial clusteringSampling cycleCase eventsPoint patterns
2012
Where science meets policy: comparing longitudinal and cross-sectional designs to address diarrhoeal disease burden in the developing world
Markovitz A, Goldstick J, Levy K, Cevallos W, Mukherjee B, Trostle J, Eisenberg J. Where science meets policy: comparing longitudinal and cross-sectional designs to address diarrhoeal disease burden in the developing world. International Journal Of Epidemiology 2012, 41: 504-513. PMID: 22253314, PMCID: PMC3324455, DOI: 10.1093/ije/dyr194.Peer-Reviewed Original ResearchConceptsCross-sectional studyCross-sectional designEffect estimatesLongitudinal studyRisk factorsDisease risk factorsRisk factor distributionInforming public health policyPublic health policiesPublic health communityRisk factor effectsHousehold risk factorsDiarrhoeal disease burdenFactor effect estimatesHealth policyDiarrhoeal disease surveillanceEcuadorian villageNational policy decisionsHealth communityDisease burdenCross-sectionDisease surveillanceFactor distributionRiskGeographic regions