Comprehensive Profiling of Social Mixing Patterns in Resource Poor Countries
Comprehensive Profiling of Social Mixing Patterns in Resource Poor Countries
批准号:
10610730
负责人:
Benjamin A Lopman
金额:
$50.45万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
未结题
起止时间:
2019-06-19 至 2025-03-31
关键词:
Africa South of the SaharaAgeAge MonthsAsiaBirth OrderCentral AmericaCessation of lifeChildChildhoodCollaborationsCommunicable DiseasesCommunitiesCountryDataDatabasesDecision MakingDevelopmentDevicesDiseaseDocumentationEffectivenessEnsureEnteralEuropeanGeographic LocationsGeographyGoalsGovernmentGuatemalaHealth PolicyHerd ImmunityHospitalizationHouseholdImmunityImmunization ProgramsIndiaIndividualInequityInfantInfectionInfluentialsInfrastructureInterventionInvestmentsLocationLow Income PopulationLow incomeMeasurementMethodsModelingMorbidity - disease rateMozambiquePakistanPatternPersonsPlayPoliciesPopulationPredispositionRecording of previous eventsResearch PersonnelResolutionResourcesRespiratory DiseaseRoleRuralRural PopulationSeasonsSiteSocial InteractionSocial SciencesStandardizationSubgroupSystemUrban PopulationVaccinatedVaccinesVulnerable Populationsage groupdata accessdata sharingdiariesdisease transmissiondisorder controlinfectious disease modelinnovationlow and middle-income countriesmathematical modelmemberopen datapublic databaserural settingsexsocialsocial contactsocial determinantssocial influencetooltransmission processurban setting
中文摘要
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英文摘要
PROJECT SUMMARY/ABSTRACT
Dynamic transmission models of infectious diseases are increasingly influential for
developing interventions and informing policy. Infectious disease transmissibility and
hence, the effectiveness of control strategies, is strongly influenced by social
interactions. Consequently, accurate data on social contact rates and mixing patterns
are fundamental parameters in the calculation of the force of infection (i.e. the rate of
susceptible individuals becoming infected). Despite the strong role social mixing
patterns play in the accurate parameterization of mathematical models, these data
remain limited, particularly in low and middle-income countries (LMICs). There are also
limited data on the social interactions of young infants that are too young to be
vaccinated or the diversity in patterns between rural and urban populations at the
community level, which are important factors for understanding infectious disease
transmission.
We propose the first multi-site study with the overall goal to use standardized methods to
collect social contact data from urban and rural populations in LMICs. Special focus will
be given to study the social interactions of infants less than six months of age. Data will
be rigorously collected from four different LMICs: Guatemala, Pakistan, India and
Mozambique. We will use standardized social contact diaries to characterize the patterns
of social contacts and mixing across the age range in urban and rural LMIC settings. We
will also comprehensively profile the social contacts of infants with their household
members in LMICs by analyzing high resolution measurements collected using wearable
proximity-sensing devices.
Moreover, through this project, we will create a database of social mixing data on LMIC
populations. We will make this database publicly available using contemporary standards
in Open Access data sharing and documentation. These data can be used by infectious
disease modelers and other researchers in the biomedical and social science
communities.
期刊论文(7)
专著(0)
科研奖励(0)
会议论文
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Comprehensive profiling of social mixing patterns in resource poor countries: a mixed methods research protocol.
资源匮乏国家社会混合模式的综合分析:混合方法研究协议。
DOI:
10.1101/2023.12.05.23299472
发表时间:
2023
期刊:
medRxiv : the preprint server for health sciences
影响因子:
--
作者:
[Aguolu,ObianujuGenevieve, Kiti,MosesChapa, Nelson,Kristin, Liu,CarolY, Sundaram,Maria, Gramacho,Sergio, Jenness,Samuel, Melegaro,Alessia, Sacoor,Charfudin, Bardaji,Azucena, Macicame,Ivalda, Jose,Americo, Cavele,Nilzio, Amosse,Felizarda, U]
通讯作者:
U
DOI:
10.1097/ede.0000000000001412
发表时间:
2021-11-01
期刊:
Epidemiology (Cambridge, Mass.)
影响因子:
--
作者:
[Liu CY, Berlin J, Kiti MC, Del Fava E, Grow A, Zagheni E, Melegaro A, Jenness SM, Omer SB, Lopman B, Nelson K]
通讯作者:
Nelson K
Changing social contact patterns among US workers during the COVID-19 pandemic: April 2020 to December 2021.
COVID-19 大流行期间美国工人社交接触模式的变化:2020 年 4 月至 2021 年 12 月。
DOI:
10.1101/2022.12.19.22283700
发表时间:
2022
期刊:
medRxiv : the preprint server for health sciences
影响因子:
--
作者:
[Kiti,MosesC, Aguolu,ObianujuG, Zelaya,Alana, Chen,HolinY, Ahmed,Noureen, Battross,Jonathan, Liu,CarolY, Nelson,KristinN, Jenness,SamuelM, Melegaro,Alessia, Ahmed,Faruque, Malik,Fauzia, Omer,SaadB, Lopman,BenA]
通讯作者:
Lopman,BenA
DOI:
10.1016/j.epidem.2021.100488
发表时间:
2021-12
期刊:
Epidemics
影响因子:
3.8
作者:
[Jenness SM, Willebrand KS, Malik AA, Lopman BA, Omer SB]
通讯作者:
Omer SB
DOI:
10.1016/j.epidem.2021.100481
发表时间:
2021-09
期刊:
Epidemics
影响因子:
3.8
作者:
[Kiti MC, Aguolu OG, Liu CY, Mesa AR, Regina R, Woody M, Willebrand K, Couzens C, Bartelsmeyer T, Nelson KN, Jenness S, Riley S, Melegaro A, Ahmed F, Malik F, Lopman BA, Omer SB]
通讯作者:
Omer SB
COVID-19 - Global Mix / Investigation of COVID-19 Disease Parameters for Transmission Models in Low-Resource Settings
-
批准号:10367612
-
项目类别:
-
资助金额:$78.58万
-
财政年份:2022
-
负责人:Benjamin A Lopman
-
依托单位:
COVID-19 - Global Mix / Investigation of COVID-19 Disease Parameters for Transmission Models in Low-Resource Settings
-
批准号:10577833
-
项目类别:
-
资助金额:$27.01万
-
财政年份:2022
-
负责人:Benjamin A Lopman
-
依托单位:
COVID Global Mix - Global Mix / Investigation of COVID-19 Disease Parameters for Transmission Models in Low-Resource Settings
-
批准号:10863617
-
项目类别:
-
资助金额:$42.9万
-
财政年份:2022
-
负责人:Benjamin A Lopman
-
依托单位:
Comprehensive Profiling of Social Mixing Patterns in Resource Poor Countries
-
批准号:10397072
-
项目类别:
-
资助金额:$52.93万
-
财政年份:2019
-
负责人:Benjamin A Lopman
-
依托单位:
Integrating data streams with multi-scale modeling to guide norovirus vaccine decision-making
-
批准号:10160920
-
项目类别:
-
资助金额:$34.03万
-
财政年份:2018
-
负责人:Benjamin A Lopman
-
依托单位:
Integrating data streams with multi-scale modeling to guide norovirus vaccine decision-making
-
批准号:10413200
-
项目类别:
-
资助金额:$34.03万
-
财政年份:2018
-
负责人:Benjamin A Lopman
-
依托单位:
Modeling ongoing SARS-CoV2 vaccination strategies in light of emerging data on immunity and viral evolution
-
批准号:10398368
-
项目类别:
-
资助金额:$17.31万
-
财政年份:2018
-
负责人:Benjamin A Lopman
-
依托单位:
国内基金
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