Gianluca Boo
Dados Biográficos
| ID | 748192 |
|---|---|
| NOME | Gianluca Boo |
| PRENOMES | Gianluca |
| SOBRENOME | Boo |
| ASSINATURA | BOO G |
| AFILIAÇÕES | University of Southampton |
| ORCID | 0000-0002-4078-8221 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 3 |
| TOTAL DE CITAÇÕES | 17 |
| TOTAL COMO AUTOR | 3 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2020 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2025 |
| ÍNDICE H | 2 |
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…
La population vue du ciel
Le dénombrement de la population, dénominateur de nombreux indicateurs statistiques, est crucial pour les politiques publiques d'un pays. Il est du ressort des instituts nationaux de statistique d'en organiser la collecte, le plus souvent par le biais d'un recensement. Que se passe-t-il lorsqu'une partie du territoire n'est pas accessible aux agents recenseurs ? Actuellement, les données spatiales, telles qu'extraites de l'imagerie satellite, off…
Need for an Integrated Deprived Area "Slum" Mapping System (Ideamaps) in Low- and Middle-Income Countries (LMICs)
Ninety percent of the people added to the planet over the next 30 years will live in African and Asian cities, and a large portion of these populations will reside in deprived neighborhoods defined by slum conditions, informal settlement, or inadequate housing. The four current approaches to neighborhood deprivation mapping are largely siloed, and each fall short of producing accurate, timely, and comparable maps that reflect local contexts. The …
Need for an Integrated Deprived Area "Slum" Mapping System (Ideamaps) in Low- and Middle-Income Countries (LMICs)
Ninety percent of the people added to the planet over the next 30 years will live in African and Asian cities, and a large portion of these populations will reside in deprived neighborhoods defined by slum conditions, informal settlement, or inadequate housing. The four current approaches to neighborhood deprivation mapping are largely siloed, and each fall short of producing accurate, timely, and comparable maps that reflect local contexts. The …
La population vue du ciel
Le dénombrement de la population, dénominateur de nombreux indicateurs statistiques, est crucial pour les politiques publiques d'un pays. Il est du ressort des instituts nationaux de statistique d'en organiser la collecte, le plus souvent par le biais d'un recensement. Que se passe-t-il lorsqu'une partie du territoire n'est pas accessible aux agents recenseurs ? Actuellement, les données spatiales, telles qu'extraites de l'imagerie satellite, off…
Need for an Integrated Deprived Area "Slum" Mapping System (Ideamaps) in Low- and Middle-Income Countries (LMICs)
Ninety percent of the people added to the planet over the next 30 years will live in African and Asian cities, and a large portion of these populations will reside in deprived neighborhoods defined by slum conditions, informal settlement, or inadequate housing. The four current approaches to neighborhood deprivation mapping are largely siloed, and each fall short of producing accurate, timely, and comparable maps that reflect local contexts. The …
La population vue du ciel
Le dénombrement de la population, dénominateur de nombreux indicateurs statistiques, est crucial pour les politiques publiques d'un pays. Il est du ressort des instituts nationaux de statistique d'en organiser la collecte, le plus souvent par le biais d'un recensement. Que se passe-t-il lorsqu'une partie du territoire n'est pas accessible aux agents recenseurs ? Actuellement, les données spatiales, telles qu'extraites de l'imagerie satellite, off…
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…
Geography (3 obras) · Impact of Light on Environment and Health (3 obras) · Economics (2 obras) · Environmental health (2 obras) · Land Use and Ecosystem Services (2 obras) · Medicine (2 obras) · Population (2 obras) · Art (1 obras) · Bayesian probability (1 obras) · Cartography (1 obras)