The science around the use of masks by the public to impede COVID-19 transmission is advancing rapidly. In this narrative review, we develop an analytical framework to examine mask usage, synthesizing the relevant literature to inform multiple areas: population impact, transmission characteristics, source control, wearer protection, sociological considerations, and implementation considerations. A primary route of transmission of COVID-19 is via respiratory particles, and it is known to be transmissible from presymptomatic, paucisymptomatic, and asymptomatic individuals. Reducing disease spread requires two things: limiting contacts of infected individuals via physical distancing and other measures and reducing the transmission probability per contact. The preponderance of evidence indicates that mask wearing reduces transmissibility per contact by reducing transmission of infected respiratory particles in both laboratory and clinical contexts. Public mask wearing is most effective at reducing spread of the virus when compliance is high. Given the current shortages of medical masks, we recommend the adoption of public cloth mask wearing, as an effective form of source control, in conjunction with existing hygiene, distancing, and contact tracing strategies. Because many respiratory particles become smaller due to evaporation, we recommend increasing focus on a previously overlooked aspect of mask usage: mask wearing by infectious people (“source control”) with benefits at the population level, rather than only mask wearing by susceptible people, such as health care workers, with focus on individual outcomes. We recommend that public officials and governments strongly encourage the use of widespread face masks in public, including the use of appropriate regulation.

Studies on the burden of human monkeypox in the Democratic Republic of the Congo (DRC) were last conducted from 1981 to 1986. Since then, the population that is immunologically naïve to orthopoxviruses has increased significantly due to cessation of mass smallpox vaccination campaigns. To assess the current risk of infection, we analyzed human monkeypox incidence trends in a monkeypox-enzootic region. Active, population-based surveillance was conducted in nine health zones in central DRC. Epidemiologic data and biological samples were obtained from suspected cases. Cumulative incidence (per 10,000 population) and major determinants of infection were compared with data from active surveillance in similar regions from 1981 to 1986. Between November 2005 and November 2007, 760 laboratory-confirmed human monkeypox cases were identified in participating health zones. The average annual cumulative incidence across zones was 5.53 per 10,000 (2.18–14.42). Factors associated with increased risk of infection included: living in forested areas, male gender, age < 15, and no prior smallpox vaccination. Vaccinated persons had a 5.2-fold lower risk of monkeypox than unvaccinated persons (0.78 vs. 4.05 per 10,000). Comparison of active surveillance data in the same health zone from the 1980s (0.72 per 10,000) and 2006–07 (14.42 per 10,000) suggests a 20-fold increase in human monkeypox incidence. Thirty years after mass smallpox vaccination campaigns ceased, human monkeypox incidence has dramatically increased in rural DRC. Improved surveillance and epidemiological analysis is needed to better assess the public health burden and develop strategies for reducing the risk of wider spread of infection.

Monkeypox virus is a zoonotic virus endemic to Central Africa. Although active disease surveillance has assessed monkeypox disease prevalence and geographic range, information about virus diversity is lacking. We therefore assessed genome diversity of viruses in 60 samples obtained from humans with primary and secondary cases of infection from 2005 through 2007. We detected 4 distinct lineages and a deletion that resulted in gene loss in 10 (16.7%) samples and that seemed to correlate with human-to-human transmission (p = 0.0544). The data suggest a high frequency of spillover events from the pool of viruses in nonhuman animals, active selection through genomic destabilization and gene loss, and increased disease transmissibility and severity. The potential for accelerated adaptation to humans should be monitored through improved surveillance. <!-- link to audio presentation here --> <!--[if!IE]> <!--> Download MP3 <!--> <![endif]--> <!--[if IE]> Download MP3 <![endif]--> Length: 1:11

The national census is an essential data source to support decision-making in many areas of public interest. However, this data may become outdated during the intercensal period, which can stretch up to several decades. In this study, we develop a Bayesian hierarchical model leveraging recent household surveys and building footprints to produce up-to-date population estimates. We estimate population totals and age and sex breakdowns with associated uncertainty measures within grid cells of approximately 100 m in five provinces of the Democratic Republic of the Congo, a country where the last census was completed in 1984. The model exhibits a very good fit, with anR²value of 0.79 for out-of-sample predictions of population totals at the microcensus-cluster level and 1.00 for age and sex proportions at the province level. This work confirms the benefits of combining household surveys and building footprints for high-resolution population estimation in countries with outdated censuses.