tetano
Editor, Senior Moderator
BMC Med. 2018 Sep 26;16(1):162. doi: 10.1186/s12916-018-1152-1.
[h=1]Quantifying the impact of social groups and vaccination on inequalities in infectious diseases using a mathematical model.[/h] Munday JD[SUP]1,[/SUP][SUP]2[/SUP], van Hoek AJ[SUP]3,[/SUP][SUP]4,[/SUP][SUP]5[/SUP], Edmunds WJ[SUP]3,[/SUP][SUP]4[/SUP], Atkins KE[SUP]3,[/SUP][SUP]4,[/SUP][SUP]6[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] [h=4]BACKGROUND:[/h] Social and cultural disparities in infectious disease burden are caused by systematic differences between communities. Some differences have a direct and proportional impact on disease burden, such as health-seeking behaviour and severity of infection. Other differences-such as contact rates and susceptibility-affect the risk of transmission, where the impact on disease burden is indirect and remains unclear. Furthermore, the concomitant impact of vaccination on such inequalities is not well understood.
[h=4]METHODS:[/h] To quantify the role of differences in transmission on inequalities and the subsequent impact of vaccination, we developed a novel mathematical framework that integrates a mechanistic model of disease transmission with a demographic model of social structure, calibrated to epidemiologic and empirical social contact data.
[h=4]RESULTS:[/h] Our model suggests realistic differences in two key factors contributing to the rates of transmission-contact rate and susceptibility-between two social groups can lead to twice the risk of infection in the high-risk population group relative to the low-risk population group. The more isolated the high-risk group, the greater this disease inequality. Vaccination amplified this inequality further: equal vaccine uptake across the two population groups led to up to seven times the risk of infection in the high-risk group. To mitigate these inequalities, the high-risk population group would require disproportionately high vaccination uptake.
[h=4]CONCLUSION:[/h] Our results suggest that differences in contact rate and susceptibility can play an important role in explaining observed inequalities in infectious diseases. Importantly, we demonstrate that, contrary to social policy intentions, promoting an equal vaccine uptake across population groups may magnify inequalities in infectious disease risk.
[h=4]KEYWORDS:[/h] Inequality; Influenza; Mathematical modelling; Rubella; Social groups; Vaccination
PMID: 30253772 PMCID: PMC6156851 DOI: 10.1186/s12916-018-1152-1
Free PMC Article
[h=1]Quantifying the impact of social groups and vaccination on inequalities in infectious diseases using a mathematical model.[/h] Munday JD[SUP]1,[/SUP][SUP]2[/SUP], van Hoek AJ[SUP]3,[/SUP][SUP]4,[/SUP][SUP]5[/SUP], Edmunds WJ[SUP]3,[/SUP][SUP]4[/SUP], Atkins KE[SUP]3,[/SUP][SUP]4,[/SUP][SUP]6[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] [h=4]BACKGROUND:[/h] Social and cultural disparities in infectious disease burden are caused by systematic differences between communities. Some differences have a direct and proportional impact on disease burden, such as health-seeking behaviour and severity of infection. Other differences-such as contact rates and susceptibility-affect the risk of transmission, where the impact on disease burden is indirect and remains unclear. Furthermore, the concomitant impact of vaccination on such inequalities is not well understood.
[h=4]METHODS:[/h] To quantify the role of differences in transmission on inequalities and the subsequent impact of vaccination, we developed a novel mathematical framework that integrates a mechanistic model of disease transmission with a demographic model of social structure, calibrated to epidemiologic and empirical social contact data.
[h=4]RESULTS:[/h] Our model suggests realistic differences in two key factors contributing to the rates of transmission-contact rate and susceptibility-between two social groups can lead to twice the risk of infection in the high-risk population group relative to the low-risk population group. The more isolated the high-risk group, the greater this disease inequality. Vaccination amplified this inequality further: equal vaccine uptake across the two population groups led to up to seven times the risk of infection in the high-risk group. To mitigate these inequalities, the high-risk population group would require disproportionately high vaccination uptake.
[h=4]CONCLUSION:[/h] Our results suggest that differences in contact rate and susceptibility can play an important role in explaining observed inequalities in infectious diseases. Importantly, we demonstrate that, contrary to social policy intentions, promoting an equal vaccine uptake across population groups may magnify inequalities in infectious disease risk.
[h=4]KEYWORDS:[/h] Inequality; Influenza; Mathematical modelling; Rubella; Social groups; Vaccination
PMID: 30253772 PMCID: PMC6156851 DOI: 10.1186/s12916-018-1152-1
Free PMC Article