Search

In the United States, studies have indicated that risk for nontuberculous mycobacterial pulmonary disease (NTM-PD) differs by geographic location and ethnic group (1). Nontuberculous mycobacteria are environmental bacteria that are [...]

Nontuberculous mycobacteria (NTM) are opportunistic environmental pathogens that can cause chronic lung disease (2,2). NTM are identified through laboratory testing for acid-fast bacilli, which test for all mycobacteria, including Mycobacterium [...]

We studied 31 US healthcare facilities to characterize trends in mycobacterial testing. During 2009-2015, testing for acid-fast bacilli increased 3.2% annually, and prevalence of pathogenic nontuberculous mycobacteria increased 4.5% annually. These increases were highest for subpopulations at high risk of infection, including older women, Asians, and patients with concurrent conditions. [ABSTRACT FROM AUTHOR]

Close contact between people is the primary route for transmission of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19). We sought to quantify interpersonal contact at the population-level by using anonymized mobile device geolocation data. We computed the frequency of contact (within six feet) between people in Connecticut during February 2020 - January 2021. Then we aggregated counts of contact events by area of residence to obtain an estimate of the total intensity of interpersonal contact experienced by residents of each town for each day. When incorporated into a susceptible-exposed-infective-removed (SEIR) model of COVID-19 transmission, the contact rate accurately predicted COVID-19 cases in Connecticut towns during the timespan. The pattern of contact rate in Connecticut explains the large initial wave of infections during March-April, the subsequent drop in cases during June-August, local outbreaks during August-September, broad statewide resurgence during September-December, and decline in January 2021. Contact rate data can help guide public health messaging campaigns to encourage social distancing and in the allocation of testing resources to detect or prevent emerging local outbreaks more quickly than traditional case investigation., One Sentence Summary: Close interpersonal contact measured using mobile device location data explains dynamics of COVID-19 transmission in Connecticut during the first year of the pandemic.