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Tracking the dynamics and spread of COVID-19 is critical to mounting an effective response to the pandemic. In the absence of randomized representative serological surveys, many SARS-CoV-2 serosurveillance studies have relied on convenience sampling to estimate cumulative incidence. One common approach is to recruit at frequently visited community locations (“venue-based” sampling), but the sources of bias and uncertainty associated with this strategy are still poorly understood. Here, we used data from a venue-based community serosurveillance study, GPS-estimated foot traffic data, and data on confirmed COVID-19 cases to report an estimate of cumulative incidence in Somerville, Massachusetts, and a methodological strategy to quantify and reduce uncertainty in serology-based cumulative incidence estimates obtained via convenience sampling. The mismatch between the geographic distribution of participants’ home locations (the “participant catchment distribution”) and the geographic distribution of infections is an important determinant of uncertainty in venue-based and other convenience sampling strategies. We found that uncertainty in cumulative incidence estimates can vary by a factor of two depending how well the participant catchment distribution matches the known or expected geographic distribution of prior infections. GPS-estimated business foot traffic data provides an important proxy measure for the participant catchment area and can be used to select venue locations that minimize uncertainty in cumulative incidence.

Additional file 1. Supplementary materials.

Background: As COVID-19 continues to spread around the world, understanding how patterns of human mobility and connectivity affect outbreak dynamics, especially before outbreaks establish locally, is critical for informing response efforts. Methods: Here, in collaboration with Facebook Data for Good, we built metapopulation models that incorporate human movement data with the goals of identifying the high risk areas of disease spread and assessing the potential effects of local travel restrictions in Taiwan. We compared the impact of intracity vs. intercity travel restrictions on both the total number of infections and the speed of outbreak spread and developed an interactive application that allows users to vary inputs and assumptions. Findings: We found that intracity travel reductions have a higher impact on overall infection numbers than intercity travel reductions, while intercity travel reductions can narrow the scope of the outbreak and help target resources. We also identified the most highly connected areas that may serve as sources of importation during an outbreak. The timing, duration, and level of travel reduction together determine the impact of travel reductions on the number of infections, and multiple combinations of these can result in similar impact. Interpretation: In Taiwan, most cases to date were imported or linked to imported cases. To prepare for the potential spread within Taiwan, we utilized Facebooks aggregated and anonymized movement and colocation data to identify cities with higher risk of infection and regional importation. Both intracity and intercity movement affect outbreak dynamics, with the former having more of an impact on the total numbers of cases and the latter impacting geographic scope. These findings have important implications for guiding future policies for travel restrictions during outbreaks in Taiwan.

Characterising connectivity between geographically separated biological populations is a common goal in many fields. Recent approaches to understanding connectivity between malaria parasite populations, with implications for disease control efforts, have used estimates of relatedness based on identity-by-descent (IBD). However, uncertainty around estimated relatedness has not been accounted for to date. IBD-based relatedness estimates with uncertainty were computed for pairs of monoclonalPlasmodium falciparumsamples collected from five cities on the Colombian-Pacific coast where long-term clonal propagation ofP. falciparumis frequent. The cities include two official ports, Buenaventura and Tumaco, that are separated geographically but connected by frequent marine traffic. The fraction of highly-related sample pairs (whose classification accounts for uncertainty) was greater within cities versus between. However, based on both the fraction of highly-related sample pairs and on a threshold-free approach (Wasserstein distances between parasite populations) connectivity between Buenaventura and Tumaco was disproportionally high. Buenaventura-Tumaco connectivity was consistent with three separate transmission events involving parasites from five different clonal components (groups of statistically indistinguishable parasites identified under a graph theoretic framework). To conclude,P. falciparumpopulation connectivity on the Colombian-Pacific coast abides by accessibility not isolation-by-distance, potentially implicating marine traffic in malaria transmission with opportunities for targeted intervention. Further investigations are required to test this and alternative hypotheses. For the first time in malaria epidemiology, we account for uncertainty around estimated relatedness (an important consideration for future studies that plan to use genotype versus whole genome sequence data to estimate IBD-based relatedness); we also use a threshold-free approach to compare parasite populations, and identify clonal components in a statistically principled manner. The approaches we employ could be adapted to other recombining organisms with mixed mating systems, thus have broad relevance.

Background Despite significant control efforts based on the large-scale distribution of insecticide treated nets, malaria cases have not declined in recent years. Mathematical models are used to predict the impact of these and other control interventions, but complex mosquito behaviors—such as repeated blood feedings—are generally not incorporated. Here, we examine how malaria transmission dynamics are impacted when infected mosquitoes feed a second time, as is typical in natural field settings. Methods We performed sporozoite time course analyses to measure the Plasmodium falciparum extrinsic incubation period (EIP) in Anopheles gambiae females blood fed once or twice. We incorporated these findings into a model of the basic reproduction number R 0 , a measure of transmission potential, using current population and monthly mean temperature data across sub-Saharan Africa. Findings A second blood feed drastically shortens the EIP and increases the average R 0 by 12.2% (range: 10.2%-56.5%), impacting hundreds of millions of people. Moreover, parasite growth is further accelerated in mosquitoes with reduced reproductive capacity, which mimic genetic modifications currently proposed in population suppression gene drives. Interpretation Our findings suggest that transmission efficiency is systematically underestimated in malaria models, particularly in elimination settings. Due to a shorter EIP, younger mosquitoes and mosquitoes with reduced reproductive ability may provide a larger contribution to infection, with important consequences for insecticide-based interventions and gene drive strategies. These findings call for an urgent reassessment of current and future control campaigns. Funding Howard Hughes Medical Institute, Bill & Melinda Gates Foundation; National Institutes of Health; National Science Foundation.

Individual quarantine and active monitoring of contacts are core disease control strategies, particularly for emerging infectious diseases such as Coronavirus Disease 2019 (COVID-19). To estimate the comparative efficacy of these interventions to control COVID-19, we fit a stochastic branching model, comparing two sets of reported parameters for the dynamics of the disease. Our results suggest that individual quarantine may contain an outbreak of COVID-19 with a short serial interval (4.8 days) only in settings with high intervention performance where at least three-quarters of infected contacts are individually quarantined. However, in settings where this performance is unrealistically high and the outbreak of COVID-19 continues to grow, so too will the burden of the number of contacts traced for active monitoring or quarantine. In such circumstances where resources are prioritized for scalable interventions such as social distancing, we show active monitoring or individual quarantine of high-risk contacts can contribute synergistically to social distancing. To the extent that interventions based on contact tracing can be implemented, therefore, they can help mitigate the spread of COVID-19. Our model highlights the urgent need for more data on the serial interval and the extent of presymptomatic transmission in order to make data-driven policy decisions regarding the cost-benefit comparisons of individual quarantine vs. active monitoring of contacts.