tetano
Editor, Senior Moderator
Theor Biol Med Model. 2019 Mar 20;16(1):6. doi: 10.1186/s12976-019-0102-8.
[h=1]Quantifying heterogeneous contact patterns in Japan: a social contact survey.[/h] Munasinghe L[SUP]1[/SUP], Asai Y[SUP]1[/SUP], Nishiura H[SUP]2[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] [h=4]BACKGROUND:[/h] Social contact surveys can greatly help in quantifying the heterogeneous patterns of infectious disease transmission. The present study aimed to conduct a contact survey in Japan, offering estimates of contact by age and location and validating a social contact matrix using a seroepidemiological dataset of influenza.
[h=4]METHODS:[/h] An internet-based questionnaire survey was conducted, covering all 47 prefectures in Japan and including a total of 1476 households. The social contact matrix was quantified assuming reciprocity and using the maximum likelihood method. By imposing several parametric assumptions for the next-generation matrix, the empirical seroepidemiological data of influenza A (H1N1) 2009 was analysed and we estimated the basic reproduction number, R[SUB]0[/SUB].
[h=4]RESULTS:[/h] In total, the reported number of contacts on weekdays was 10,682 whereas that on weekend days was 8867. Strong age-dependent assortativity was identified. Forty percent of weekday contacts took place at schools or workplaces, but that declined to 14% on weekends. Accounting for the age-dependent heterogeneity with the known social contact matrix, the minimum value of the Akaike information criterion was obtained and R[SUB]0[/SUB] was estimated at 1.45 (95% confidence interval: 1.42, 1.49).
[h=4]CONCLUSIONS:[/h] Survey datasets will be useful for parameterizing the heterogeneous transmission model of various directly transmitted infectious diseases in Japan. Age-dependent assortativity, especially among children, along with numerous contacts in school settings on weekdays implies the potential effectiveness of school closure.
[h=4]KEYWORDS:[/h] Cumulative incidence; Epidemic; Epidemiological model; Influenza; Mathematical model
PMID: 30890153 DOI: 10.1186/s12976-019-0102-8
Free full text
[h=1]Quantifying heterogeneous contact patterns in Japan: a social contact survey.[/h] Munasinghe L[SUP]1[/SUP], Asai Y[SUP]1[/SUP], Nishiura H[SUP]2[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] [h=4]BACKGROUND:[/h] Social contact surveys can greatly help in quantifying the heterogeneous patterns of infectious disease transmission. The present study aimed to conduct a contact survey in Japan, offering estimates of contact by age and location and validating a social contact matrix using a seroepidemiological dataset of influenza.
[h=4]METHODS:[/h] An internet-based questionnaire survey was conducted, covering all 47 prefectures in Japan and including a total of 1476 households. The social contact matrix was quantified assuming reciprocity and using the maximum likelihood method. By imposing several parametric assumptions for the next-generation matrix, the empirical seroepidemiological data of influenza A (H1N1) 2009 was analysed and we estimated the basic reproduction number, R[SUB]0[/SUB].
[h=4]RESULTS:[/h] In total, the reported number of contacts on weekdays was 10,682 whereas that on weekend days was 8867. Strong age-dependent assortativity was identified. Forty percent of weekday contacts took place at schools or workplaces, but that declined to 14% on weekends. Accounting for the age-dependent heterogeneity with the known social contact matrix, the minimum value of the Akaike information criterion was obtained and R[SUB]0[/SUB] was estimated at 1.45 (95% confidence interval: 1.42, 1.49).
[h=4]CONCLUSIONS:[/h] Survey datasets will be useful for parameterizing the heterogeneous transmission model of various directly transmitted infectious diseases in Japan. Age-dependent assortativity, especially among children, along with numerous contacts in school settings on weekdays implies the potential effectiveness of school closure.
[h=4]KEYWORDS:[/h] Cumulative incidence; Epidemic; Epidemiological model; Influenza; Mathematical model
PMID: 30890153 DOI: 10.1186/s12976-019-0102-8
Free full text