Mousa Andria, Winskill Peter, Watson Oliver J, Ratmann Oliver, Monod Mélodie, Ajelli Marco, Diallo Aldiouma, Dodd Peter J, Grijalva Carlos G, Kiti Moses Chapa, Krishnan Anand, Kumar Rakesh, Kumar Supriya, Kwok Kin On, Lanata Claudio F, Le Polain de Waroux Olivier, Leung Kathy, Mahikul Wiriya, Melegaro Alessia, Morrow Carl D, Mossong Joël, Neal Eleanor Fg, Nokes David J, Pan-Ngum Wirichada, Potter Gail E, Russell Fiona M, Saha Siddhartha, Sugimoto Jonathan D, Wei Wan In, Wood Robin R, Wu Joseph T, Zhang Juanjuan, Walker Patrick Gt, Whittaker Charles
MRC Centre for Global Infectious Disease Analysis; and the Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK.
Department of Mathematics, Imperial College London, London, UK.
medRxiv. 2021 Jun 15:2021.06.10.21258720. doi: 10.1101/2021.06.10.21258720.
Transmission of respiratory pathogens such as SARS-CoV-2 depends on patterns of contact and mixing across populations. Understanding this is crucial to predict pathogen spread and the effectiveness of control efforts. Most analyses of contact patterns to date have focussed on high-income settings.
Here, we conduct a systematic review and individual-participant meta-analysis of surveys carried out in low- and middle-income countries and compare patterns of contact in these settings to surveys previously carried out in high-income countries. Using individual-level data from 28,503 participants and 413,069 contacts across 27 surveys we explored how contact characteristics (number, location, duration and whether physical) vary across income settings.
Contact rates declined with age in high- and upper-middle-income settings, but not in low-income settings, where adults aged 65+ made similar numbers of contacts as younger individuals and mixed with all age-groups. Across all settings, increasing household size was a key determinant of contact frequency and characteristics, but low-income settings were characterised by the largest, most intergenerational households. A higher proportion of contacts were made at home in low-income settings, and work/school contacts were more frequent in high-income strata. We also observed contrasting effects of gender across income-strata on the frequency, duration and type of contacts individuals made.
These differences in contact patterns between settings have material consequences for both spread of respiratory pathogens, as well as the effectiveness of different non-pharmaceutical interventions.
This work is primarily being funded by joint Centre funding from the UK Medical Research Council and DFID (MR/R015600/1).
严重急性呼吸综合征冠状病毒2（SARS-CoV-2）等呼吸道病原体的传播取决于人群间的接触和混合模式。了解这一点对于预测病原体传播和防控措施的有效性至关重要。迄今为止，大多数接触模式分析都集中在高收入环境中。
在此，我们对低收入和中等收入国家开展的调查进行了系统评价和个体参与者荟萃分析，并将这些环境中的接触模式与之前在高收入国家开展的调查进行比较。利用来自27项调查的28503名参与者和413069次接触的个体层面数据，我们探讨了接触特征（数量、地点、持续时间以及是否为身体接触）在不同收入环境中的差异。
在高收入和中高收入环境中，接触率随年龄下降，但在低收入环境中并非如此，在低收入环境中，65岁及以上的成年人与年轻人的接触次数相似，且与所有年龄组混合接触。在所有环境中，家庭规模的增加是接触频率和特征的关键决定因素，但低收入环境的特点是家庭规模最大、代际关系最复杂。低收入环境中，在家中进行的接触比例更高，而在高收入阶层中，工作/学校接触更为频繁。我们还观察到不同收入阶层中性别对个体接触频率、持续时间和类型的影响存在差异。
不同环境下接触模式的这些差异对呼吸道病原体的传播以及不同非药物干预措施的有效性都有重大影响。
这项工作主要由英国医学研究理事会和国际发展部的联合中心资金资助（MR/R015600/1）。
