SARS-CoV-2等呼吸道病原体的传播取决于人群之间的接触和混合模式。了解这一点对于预测病原体传播和控制努力的有效性至关重要。迄今为止,大多数对接触模式的分析都集中在高收入环境上。
这里,我们对在低收入和中等收入国家进行的调查进行了系统回顾和个体参与者荟萃分析,并将这些环境中的接触模式与以前在高收入国家进行的调查进行了比较.使用来自27项调查的28,503名参与者和413,069名联系人的个人数据,我们探索了接触特征(数量,location,持续时间,以及是否物理)因收入设置而异。
在高收入和中高收入地区,接触率随着年龄的增长而下降,但不是在低收入环境中,65岁以上的成年人与年轻人接触的数量相似,并且与所有年龄组混合。在所有设置中,家庭规模的增加是接触频率和特征的关键决定因素,低收入环境的特点是最大的,大多数代际家庭。在低收入环境中,在家中进行接触的比例更高,工作/学校接触在高收入阶层更为频繁。我们还观察到不同收入阶层的性别对频率的对比影响,持续时间,以及个人接触的类型。
环境之间接触模式的这些差异对呼吸道病原体的传播和不同非药物干预措施的有效性都有实质性影响。
这项工作主要由英国医学研究委员会和DFID(MR/R015600/1)联合中心资助。
传染病,特别是由SARS-CoV-2等空气传播的病原体引起的,通过社会接触传播,了解人们如何混合对于控制疫情至关重要。为了探索这些模式,研究人员通常进行大型接触调查。参与者被要求提供个人信息(如性别、年龄和职业),以及最近社会接触的细节,通常是在过去24小时内发生的。这些信息包括,接触者的年龄和性别,互动发生的地方,它持续了多长时间,以及它是否涉及身体接触。这些调查有助于科学家预测传染病可能如何传播。但有一个问题:大部分数据来自高收入国家,有证据表明,不同地方的社会接触模式不同。因此,来自这些国家的数据可能对预测感染在低收入地区的传播方式没有帮助.这里,Mousaetal.收集并合并了COVID-19大流行前进行的27次接触调查的数据,以了解高收入和低收入环境之间的基线社交互动如何变化。比较显示,在高收入国家,人们每天接触的数量随着年龄的增长而减少。但是,在低收入国家,年轻人和老年人的接触数量相似,并且与所有年龄组混合.在高收入国家,更多的接触发生在工作或学校,在低收入环境中,更多的互动发生在家里,人们也更有可能生活在更大的地方,代际家庭。Mousaetal.还发现性别影响接触的持续时间以及它们是否涉及身体接触,这两者都是传播空气病原体的关键风险因素。这些发现可以帮助研究人员预测传染病如何在不同的环境中传播。它们还可以用来评估非医疗限制的有效性,比如保护老年人和关闭工作场所,将减少世界不同地区的传输。
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 focused 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, with low-income settings 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 and 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).
Infectious diseases, particularly those caused by airborne pathogens like SARS-CoV-2, spread by social contact, and understanding how people mix is critical in controlling outbreaks. To explore these patterns, researchers typically carry out large contact surveys. Participants are asked for personal information (such as gender, age and occupation), as well as details of recent social contacts, usually those that happened in the last 24 hours. This information includes, the age and gender of the contact, where the interaction happened, how long it lasted, and whether it involved physical touch. These kinds of surveys help scientists to predict how infectious diseases might spread. But there is a problem: most of the data come from high-income countries, and there is evidence to suggest that social contact patterns differ between places. Therefore, data from these countries might not be useful for predicting how infections spread in lower-income regions. Here, Mousa et al. have collected and combined data from 27 contact surveys carried out before the COVID-19 pandemic to see how baseline social interactions vary between high- and lower-income settings. The comparison revealed that, in higher-income countries, the number of daily contacts people made decreased with age. But, in lower-income countries, younger and older individuals made similar numbers of contacts and mixed with all age groups. In higher-income countries, more contacts happened at work or school, while in low-income settings, more interactions happened at home and people were also more likely to live in larger, intergenerational households. Mousa et al. also found that gender affected how long contacts lasted and whether they involved physical contact, both of which are key risk factors for transmitting airborne pathogens. These findings can help researchers to predict how infectious diseases might spread in different settings. They can also be used to assess how effective non-medical restrictions, like shielding of the elderly and workplace closures, will be at reducing transmissions in different parts of the world.