It is imperative to advance our understanding of heterogeneities in the transmission of SARS-CoV-2 such as age-specific infectiousness and superspreading. To this end, it is important to exploit multiple data streams that are becoming abundantly available during the pandemic. In this paper, we formulate an individual-level spatiotemporal mechanistic framework to integrate individual surveillance data with geolocation data and aggregate mobility data, enabling a more granular understanding of the transmission dynamics of SARS-CoV-2. We analyze reported cases, between March and early May 2020, in five (urban and rural) counties in the state of Georgia. First, our results show that the reproductive number reduced to below one in about 2 wk after the shelter-in-place order. Superspreading appears to be widespread across space and time, and it may have a particularly important role in driving the outbreak in rural areas and an increasing importance toward later stages of outbreaks in both urban and rural settings. Overall, about 2% of cases were directly responsible for 20% of all infections. We estimate that the infected nonelderly cases (<60 y) may be 2.78 [2.10, 4.22] times more infectious than the elderly, and the former tend to be the main driver of superspreading. Our results improve our understanding of the natural history and transmission dynamics of SARS-CoV-2. More importantly, we reveal the roles of age-specific infectiousness and characterize systematic variations and associated risk factors of superspreading. These have important implications for the planning of relaxing social distancing and, more generally, designing optimal control measures.

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BackgroundSerology tests can identify previous infections and facilitate estimation of the number of total infections. However, immunoglobulins targeting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been reported to wane below the detectable level of serological assays. We estimate the cumulative incidence of SARS-CoV-2 infection from serology studies, accounting for expected levels of antibody acquisition (seroconversion) and waning (seroreversion), and apply this framework using data from New York City (NYC) and Connecticut.MethodsWe estimated time from seroconversion to seroreversion and infection fatality ratio (IFR) using mortality data from March-October 2020 and population-level cross-sectional seroprevalence data from April-August 2020 in NYC and Connecticut. We then estimated the daily seroprevalence and cumulative incidence of SARS-CoV-2 infection.FindingsThe estimated average time from seroconversion to seroreversion was 3-4 months. The estimated IFR was 1.1% (95% credible interval: 1.0-1.2%) in NYC and 1.4% (1.1-1.7%) in Connecticut. The estimated daily seroprevalence declined after a peak in the spring. The estimated cumulative incidence reached 26.8% (24.2-29.7%) and 8.8% (7.1-11.3%) at the end of September in NYC and Connecticut, higher than maximum seroprevalence measures (22.1% and 6.1%), respectively.InterpretationThe cumulative incidence of SARS-CoV-2 infection is underestimated using cross-sectional serology data without adjustment for waning antibodies. Our approach can help quantify the magnitude of underestimation and adjust estimates for waning antibodies.FundingThis study was supported by the US National Science Foundation and the National Institute of Allergy and Infectious Diseases.

Introduction Immunization programs in developing countries increasingly face challenges to ensure equitable delivery of services within cities where rapid urban growth can result in informal settlements, poor living conditions, and heterogeneous populations. A number of strategies have been utilized in developing countries to ensure high community demand and equitable availability of urban immunization services; however, a synthesis of the literature on these strategies has not previously been undertaken. Methods We reviewed articles published in English in peer-reviewed journals between 1990 and 2013 that assessed interventions for improving routine immunization coverage in urban areas in low- and middle-income countries. We categorized the intervention in each study into one of three groups: (1) interventions aiming to increase utilization of immunization services; (2) interventions aiming to improve availability of immunization services by healthcare providers, or (3) combined availability and utilization interventions. We summarized the main quantitative outcomes from each study and effective practices from each intervention category. Results Fifteen studies were identified; 87% from the African, Eastern Mediterranean and Southeast Asian regions of the World Health Organization (WHO). Six studies were randomized controlled trials, eight were pre- and post-intervention evaluations, and one was a cross-sectional study. Four described interventions designed to improve availability of routine immunization services, six studies described interventions that aimed to increase utilization, and five studies aiming to improve both availability and utilization of services. All studies reported positive change in their primary outcome indicator, although seven different primary outcomes indicators were used across studies. Studies varied considerably with respect to the type of intervention assessed, study design, and length of intervention assessment. Conclusion Few studies have assessed interventions designed explicitly for the unique challenges facing immunization programs in urban areas. Further research on sustainability, scalability, and cost-effectiveness of interventions is needed to fill this gap.

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