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1.
BMC Infect Dis ; 23(1): 324, 2023 May 15.
Article in English | MEDLINE | ID: mdl-37189060

ABSTRACT

SARS-CoV-2 is primarily transmitted through person-to-person contacts. It is important to collect information on age-specific contact patterns because SARS-CoV-2 susceptibility, transmission, and morbidity vary by age. To reduce the risk of infection, social distancing measures have been implemented. Social contact data, which identify who has contact with whom especially by age and place are needed to identify high-risk groups and serve to inform the design of non-pharmaceutical interventions. We estimated and used negative binomial regression to compare the number of daily contacts during the first round (April-May 2020) of the Minnesota Social Contact Study, based on respondent's age, gender, race/ethnicity, region, and other demographic characteristics. We used information on the age and location of contacts to generate age-structured contact matrices. Finally, we compared the age-structured contact matrices during the stay-at-home order to pre-pandemic matrices. During the state-wide stay-home order, the mean daily number of contacts was 5.7. We found significant variation in contacts by age, gender, race, and region. Adults between 40 and 50 years had the highest number of contacts. The way race/ethnicity was coded influenced patterns between groups. Respondents living in Black households (which includes many White respondents living in inter-racial households with black family members) had 2.7 more contacts than respondents in White households; we did not find this same pattern when we focused on individual's reported race/ethnicity. Asian or Pacific Islander respondents or in API households had approximately the same number of contacts as respondents in White households. Respondents in Hispanic households had approximately two fewer contacts compared to White households, likewise Hispanic respondents had three fewer contacts than White respondents. Most contacts were with other individuals in the same age group. Compared to the pre-pandemic period, the biggest declines occurred in contacts between children, and contacts between those over 60 with those below 60.


Subject(s)
COVID-19 , SARS-CoV-2 , Adult , Child , Humans , COVID-19/epidemiology , COVID-19/prevention & control , Minnesota/epidemiology , Physical Distancing , Ethnicity
2.
BMC Infect Dis ; 21(1): 1009, 2021 Sep 27.
Article in English | MEDLINE | ID: mdl-34579645

ABSTRACT

BACKGROUND: Diseases such as COVID-19 are spread through social contact. Reducing social contacts is required to stop disease spread in pandemics for which vaccines have not yet been developed. However, existing data on social contact patterns in the United States (U.S.) is limited. METHOD: We use American Time Use Survey data from 2003-2018 to describe and quantify the age-pattern of disease-relevant social contacts. For within-household contacts, we construct age-structured contact duration matrices (who spends time with whom, by age). For both within-household and non-household contacts, we also estimate the mean number and duration of contact by location. We estimate and test for differences in the age-pattern of social contacts based on demographic, temporal, and spatial characteristics. RESULTS: The mean number and duration of social contacts vary by age. The biggest gender differences in the age-pattern of social contacts are at home and at work; the former appears to be driven by caretaking responsibilities. Non-Hispanic Blacks have a shorter duration of contact and fewer social contacts than non-Hispanic Whites. This difference is largely driven by fewer and shorter contacts at home. Pre-pandemic, non-Hispanic Blacks have shorter durations of work contacts. Their jobs are more likely to require close physical proximity, so their contacts are riskier than those of non-Hispanic Whites. Hispanics have the highest number of household contacts and are also more likely to work in jobs requiring close physical proximity than non-Hispanic Whites. With the exceptions of work and school contacts, the duration of social contact is higher on weekends than on weekdays. Seasonal differences in the total duration of social contacts are driven by school-aged respondents who have significantly shorter contacts during the summer months. Contact patterns did not differ by metro status. Age patterns of social contacts were similar across regions. CONCLUSION: Social contact patterns differ by age, race and ethnicity, and gender. Other factors besides contact patterns may be driving seasonal variation in disease incidence if school-aged individuals are not an important source of transmission. Pre-pandemic, there were no spatial differences in social contacts, but this finding has likely changed during the pandemic.


Subject(s)
COVID-19 , Communicable Diseases , Child , Communicable Diseases/epidemiology , Family Characteristics , Humans , SARS-CoV-2 , Social Behavior , United States/epidemiology
3.
Biodemography Soc Biol ; 61(2): 209-30, 2015.
Article in English | MEDLINE | ID: mdl-26266973

ABSTRACT

Birth month is broadly predictive of both under-5 mortality rates and stunting throughout most of sub-Saharan Africa (SSA). Observed factors, such as mother's age at birth and educational status, are correlated with birth month but are not the main factors underlying the relationship between birth month and child health. Accounting for maternal selection via a fixed-effects model attenuates the relationship between birth month and health in many SSA countries. In the remaining countries, the effect of birth month may be mediated by environmental factors. This study found that birth month effects on mortality typically do not vary across age intervals; the differential mortality rates by birth month are evident in the neonatal period and continue across age intervals. The male-to-female sex ratio at birth did not vary by birth month, which suggests that in utero exposures are not influencing fetal loss, and that therefore the birth month effects are not likely a result of selective survival during the in utero period. In one-third of the sample, the birth month effects on stunting diminished after the age of 2 years; therefore, some children were able to catch up. Policies to improve child health should target pregnant women and infants and must take seasonality into account.


Subject(s)
Child Health/statistics & numerical data , Infant Mortality , Seasons , Africa South of the Sahara/epidemiology , Child, Preschool , Female , Growth Disorders/etiology , Humans , Infant , Infant, Newborn , Male , Pregnancy , Proportional Hazards Models , Sex Ratio , Socioeconomic Factors , Survival Analysis
4.
PLoS One ; 8(10): e75806, 2013.
Article in English | MEDLINE | ID: mdl-24204580

ABSTRACT

We analyze the impact of birth seasonality (seasonal oscillations in the birth rate) on the dynamics of acute, immunizing childhood infectious diseases. Previous research has explored the effect of human birth seasonality on infectious disease dynamics using parameters appropriate for the developed world. We build on this work by including in our analysis an extended range of baseline birth rates and amplitudes, which correspond to developing world settings. Additionally, our analysis accounts for seasonal forcing both in births and contact rates. We focus in particular on the dynamics of measles. In the absence of seasonal transmission rates or stochastic forcing, for typical measles epidemiological parameters, birth seasonality induces either annual or biennial epidemics. Changes in the magnitude of the birth fluctuations (birth amplitude) can induce significant changes in the size of the epidemic peaks, but have little impact on timing of disease epidemics within the year. In contrast, changes to the birth seasonality phase (location of the peak in birth amplitude within the year) significantly influence the timing of the epidemics. In the presence of seasonality in contact rates, at relatively low birth rates (20 per 1000), birth amplitude has little impact on the dynamics but does have an impact on the magnitude and timing of the epidemics. However, as the mean birth rate increases, both birth amplitude and phase play an important role in driving the dynamics of the epidemic. There are stronger effects at higher birth rates.


Subject(s)
Birth Rate , Communicable Diseases/epidemiology , Immunization , Seasons , Africa South of the Sahara , Algorithms , Communicable Diseases/transmission , Humans , Incidence , Measles/epidemiology , Measles/transmission , Models, Statistical , Public Health Surveillance
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