patterns of human social contact and contact with animals in shanghai china CORD-Papers-2022-06-02 (Version 1)

Title: Patterns of human social contact and contact with animals in Shanghai China
Abstract: East Asia is as a principal hotspot for emerging zoonotic infections. Understanding the likely pathways for their emergence and spread requires knowledge on human-human and human-animal contacts but such studies are rare. We used self-completed and interviewer-completed contact diaries to quantify patterns of these contacts for 965 individuals in 2017/2018 in a high-income densely-populated area of China Shanghai City. Interviewer-completed diaries recorded more social contacts (19.3 vs. 18.0) and longer social contact duration (35.0 vs. 29.1 hours) than self-reporting. Strong age-assortativity was observed in all age groups especially among young participants (aged 720) and middle aged participants (2555 years). 17.7% of participants reported touching animals (15.3% (pets) 0.0% (poultry) and 0.1% (livestock)). Human-human contact was very frequent but contact with animals (especially poultry) was rare although associated with frequent human-human contact. Hence this densely populated area is more likely to act as an accelerator for human-human spread but less likely to be at the source of a zoonosis outbreak. We also propose that telephone interview at the end of reporting day is a potential improvement of the design of future contact surveys.
Published: 2019-10-22
Journal: Sci Rep
DOI: 10.1038/s41598-019-51609-8
DOI_URL: http://doi.org/10.1038/s41598-019-51609-8
Author Name: Zhang Juanjuan
Author link: https://covid19-data.nist.gov/pid/rest/local/author/zhang_juanjuan
Author Name: Klepac Petra
Author link: https://covid19-data.nist.gov/pid/rest/local/author/klepac_petra
Author Name: Read Jonathan M
Author link: https://covid19-data.nist.gov/pid/rest/local/author/read_jonathan_m
Author Name: Rosello Alicia
Author link: https://covid19-data.nist.gov/pid/rest/local/author/rosello_alicia
Author Name: Wang Xiling
Author link: https://covid19-data.nist.gov/pid/rest/local/author/wang_xiling
Author Name: Lai Shengjie
Author link: https://covid19-data.nist.gov/pid/rest/local/author/lai_shengjie
Author Name: Li Meng
Author link: https://covid19-data.nist.gov/pid/rest/local/author/li_meng
Author Name: Song Yujian
Author link: https://covid19-data.nist.gov/pid/rest/local/author/song_yujian
Author Name: Wei Qingzhen
Author link: https://covid19-data.nist.gov/pid/rest/local/author/wei_qingzhen
Author Name: Jiang Hao
Author link: https://covid19-data.nist.gov/pid/rest/local/author/jiang_hao
Author Name: Yang Juan
Author link: https://covid19-data.nist.gov/pid/rest/local/author/yang_juan
Author Name: Lynn Henry
Author link: https://covid19-data.nist.gov/pid/rest/local/author/lynn_henry
Author Name: Flasche Stefan
Author link: https://covid19-data.nist.gov/pid/rest/local/author/flasche_stefan
Author Name: Jit Mark
Author link: https://covid19-data.nist.gov/pid/rest/local/author/jit_mark
Author Name: Yu Hongjie
Author link: https://covid19-data.nist.gov/pid/rest/local/author/yu_hongjie
sha: a1ccc7fe4c6c4ae77f84bb48011f0ee0b5900045
license: cc-by
license_url: https://creativecommons.org/licenses/by/4.0/
source_x: Medline; PMC
source_x_url: https://www.medline.com/https://www.ncbi.nlm.nih.gov/pubmed/
pubmed_id: 31641189
pubmed_id_url: https://www.ncbi.nlm.nih.gov/pubmed/31641189
pmcid: PMC6805924
pmcid_url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6805924
url: https://www.ncbi.nlm.nih.gov/pubmed/31641189/ https://doi.org/10.1038/s41598-019-51609-8
has_full_text: TRUE
Keywords Extracted from Text Content: people Supplementary Table S13 76y Supplementary Fig. S24 smooth Human-to-animal contacts Supplementary Fig. S5 A Workdays matrix adolescents __________________________________ alpha equals 0.05 Peru 7 Human-to-human contacts Fig. 2 B1-B2 contacts Shanghai Supplementary Table S9 75y dogs left 20-39y log(1 participants Supplementary Fig. S23 people France 6 POLYMOD 2 Supplementary Text S10 GAM children Fig. 2 C1-C2 contact matrix ICC age-mixed human contact matrices Fig. S5 B line
Extracted Text Content in Record: First 5000 Characters:We first sampled three central urban districts, then sampled a total of ten subdistricts within those three central urban districts, and from each of those ten subdistricts we sampled four neighborhoods (the smallest administrative unit in China, with a mean population of 3800 people per neighborhood sampled), using multi-stage stratified probability proportional to population size (PPS). At the district level, three districts were sampled from the total seven central urban districts of Shanghai by PPS (Huangpu, Xuhui, and Changning). At the subdistrict level, ten subdistricts within those three central urban districts were sampled by PPS, where the number of subdistricts needed per district was determined by proportionate stratification (four from Xuhui, three from Huangpu, and three from Changning). At the household level, 25 households per neighborhood were selected with the help of neighborhood committee cadres. The selection of households was encouraged to be broadly representative of the population of the neighborhood in terms of geographical spread. One person per household was invited to participate in our study until we met our predefined target sizes by age and gender (described below, table A). A pilot survey was conducted between December 2017 and January 2018, with two of the selected neighborhoods as study sites. Sample size allocation at each stage had to do with the sample size calculation, which was described below. The sample size was calculated based on the key variable -"the number of daily contacts". We assumed that intra-class correlation among individuals only existed at neighborhood level, not at subdistrict and not even at district. Comparing our complex sample with an unrestricted sample design, we accounted for clustering at neighborhood level, by multiplying the effective sample size by the design effect. Hence the sample size calculation was as follows: Assumptions for the sample size calculation: • 95% confidence, alpha equals 0.05. • Sigma equals 6.78, referring to a published social contact survey in Hong Kong 1 , as Shanghai may have similar characteristics of high population density and connectivity to Hong Kong. • Delta equals 0.6, a specified level of precision. • 1 / 2 equals 25, based on our budget. • equals 0.03, assuming equal ICC across clusters ( ̅ = ). There was no published data about ICC to be used in our social contact study, so we estimated it according to our pilot study results. Based on the above assumptions, a total sample size of 894 was required. Assuming that 90% of the participants would eventually return a completed survey, we need recruit approximately 1,000 participants for the study. In this case, as b equaled 25, 25 households were needed per neighborhood, and thus forty neighborhoods were needed in total. Four neighborhoods were sampled per subdistrict, thus a total of ten subdistricts were required for the three central districts. According to proportionate stratified PPS, we sampled four subdistricts in Xuhui, three in Changning and three for Huangpu. Eight age groups were defined as 0-9, 10-19, 20-29, 30-39, 40-49, 50-59, 60-69, 70 years and above. Considering the final sample size of 1000, we aimed for each age group to contain 125 individuals. In addition, children and adolescents younger than 20 years old were oversampled because they were considered to be the main driver for transmission of many infectious respiratory diseases (as in 2 ). Table A showed the age distribution of the population of Shanghai (central urban districts) in 2017 (in which the total population size is about 7.3 million) compared with that in our sample. More practically, inclusion criteria for the study were 1) a Chinese person who had been living in Shanghai for longer than two weeks and did not intend to move from Shanghai in the following two weeks, 2) being able to move independently and understand clearly the content of our questionnaire, and 3) giving written individual informed consent (from a parent/guardian if participant was below 18 years of age). Recall bias. In order to explore recall bias at the end of H-H section, we asked questions to assess participants' memory such as "How well do you recall your contacts today?". There were five options for selection, including "very well", "well", "moderately well", "not well" and "poorly". Additionally, participants were required to estimate approximately how many people they might have accidentally forgotten to include (Supplementary Text S12; questions 17-18.). This information is important to evaluate the quality of data collection. Tips on filling in the questionnaire. If the same person was encountered several times during the assigned day, participants were instructed to only record him/her once, and to record the total time participants spent with that person over the entire day. Reporting a group contact involved reporting the total (approximate) size of the group and the age range of the majority in the
Keywords Extracted from PMC Text: Australia23,24 weekday/weekend review41 Supplementary Text S4 POLYMOD10 Supplementary Text S3 Workdays dogs people 10,240 cattle Supplementary Fig. S16 rabies cases43 regions44 Guangzhou28 Supplementary Table S13 Japan26 Shanghai. wounds 6,953 East Asia1 H-H contact matrix children Shanghai, China Supplementary Fig. S11 human barrier H-A Supplementary Table S8 humans swine Supplementary Text S7 studies10,12,13,18,21,28,31,35,40 Shanghai since 7–9 Uganda21 interviewer-led Supplementary Table S6 conclusions9 3–6 y Shanghai City Supplementary Table S14 Kwok al.31 poultry livestock Shanghai42 A/H1N1 6,790 people contact2 MatchIt al.40 Supplementary Text S10 assortativity37 Supplementary Figs S9 pre-agreed Supplementary Table S7 Supplementary Text S9 questionnaires41 Supplementary Fig. S15 human contact matrices Shanghai download32 Russia22 animal-human human left Indonesia)15,16 stem bites Supplementary Fig. S5 modes10,14,45 matrix households33 's Supplementary Fig. S23 Kenya20 human-human contact 50–54 y 45–49 human-to-animal H-A contact Supplementary Figs S7 Supplementary Text S8 Belgium35 study35 20–60 human-human ( Supplementary Figs S21 Supplementary Figs S17 cats S10 S22 Supplementary Text S12 20–59 contacts schools34 Shanghai36 Peru25 diaries24,29 Supplementary Fig. S6 contact matrix Supplementary Tables S10 studies41 Supplementary Table S9 line S18 diseases1 Supplementary Fig. S13 A(H7N9 human-human out-of-subdistrict 30–40 " participants rabies 55–59 y Supplementary Table S3 coronavirus Supplementary Fig. S12 Supplementary Fig. S14 60–64 y, 65–69 H-A contacts individuals respondents
Extracted PMC Text Content in Record: First 5000 Characters:Most of the major global infectious disease threats of the last decade (including epidemics of pandemic influenza A/H1N1, Middle East respiratory syndrome coronavirus and Ebola) have emerged from pathogens crossing the species barrier from animals to humans. A principal hotspot for such disease emergence is the megacities of East Asia1. For these diseases, successful establishment in human populations is dictated by both animal-to-human (most notably with domesticated animals raised in agricultural settings such as poultry, swine and cattle) and human-to-human contact2. However, studies measuring and characterizing contacts on human-animal interface and subsequent transmission among humans are scarce. For emerging pathogens with established human-human transmission, the spread or even outbreak in humans will be driven by patterns of human encounters, which can also determine the effectiveness of interventions against them (e.g. vaccination, contact tracing and social distancing)3. Patterns of human encounters are location specific, therefore improving local intervention strategies relies on understanding local patterns of social contact4–8. There are still, however, relatively few empirical studies of age-specific social contacts which integrate location, animal contact data, and the interaction between human-human and human-animal contact. Furthermore, an evaluation of public health strategies that is based on social contact information derived from a different country that might not be representative of local mixing and may result in erroneous conclusions9. China is a large, diverse country with rapid economic development, high urbanization, and frequent interaction between humans and animals. The richest and most populous city is Shanghai with a population of 24 million. We used two types of questionnaire delivery (self-completed and telephone interview) to quantify social contact patterns in Shanghai City, which is a hub for spreading infectious diseases due to its high population density and connectivity of the air transportation network. Large population-based surveys of age-specific social contacts exists for several European countries10–14 and are increasingly conducted in low- and middle-income Asian (Thailand, Vietnam and Indonesia)15,16 and African countries (Zimbabwe and South Africa17–19, Kenya20, Uganda21). There have also been similar surveys in Russia22, Australia23,24, Peru25, Japan26, Taiwan27, southern China (Guangzhou28, Hong Kong29–31). Data from such contact studies are increasingly made freely available for download32. These surveys have their limitations, so recently there have been proposals for improved designs that would measure social contact patterns with less recall bias. Recent technological developments allow the measurement of human proximity and social interactions using wearable sensors, but such surveys are limited to specific settings, such as households33 or schools34 and require high levels of participation within such settings to succeed. Some studies encouraged participants to record each contact as it occurred11,17,20,29, but such prospectively recording has been found difficult to do (e.g. less than 5% participants completed the questionnaire prospectively in a study by Leung et al.29). Two most common modes of data collection are self-reporting (in form of diary, for example) and interviewer-led (the interviewer may record information in a diary for the subject), typically collecting information retrospectively. A possible way to minimize recall bias is to perform interviews on the day of reporting. Comparing results from such an interview to purely self-reported data allows assessment of the bias in studies that rely entirely on self-reporting without any memory aids. Such studies are rare and to our knowledge none assess consistency between self-reporting studies and telephone interviews. Another gap we identified involves characterizing and measuring human-animal contact. We identified a single study that considers human-human and human-animal contact patterns in Belgium35. However, detailed contact characteristics such as human-human contact duration, number of contact settings, human-to-animal touching duration, and contact matrix were not reported. Our current study has three aims: (i) quantify local human-human (H-H) and human-animal (H-A) contacts in an urban setting in China, (ii) explore the interaction between H-H and H-A contact, and (iii) assess consistency between two different modes of data-collection, self-reporting and telephone interview-led studies. The survey was carried out between December 2017 and May 2018 in Shanghai, a city in the southeast of China (Supplementary Fig. S1). The central urban districts of Shanghai were selected as our study sites, representing typical urban areas with high income and high population density (Supplementary Fig. S2). The 7 central urban districts are defined as areas within the outer ring road of Shanghai36,
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