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Existing acute febrile illness (AFI) surveillance systems can be leveraged to identify and characterize emerging pathogens, such as SARS-CoV-2, which causes COVID-19. The US Centers for Disease Control and Prevention collaborated with ministries of health and implementing partners in Belize, Ethiopia, Kenya, Liberia, and Peru to adapt AFI surveillance systems to generate COVID-19 response information. Staff at sentinel sites collected epidemiologic data from persons meeting AFI criteria and specimens for SARS-CoV-2 testing. A total of 5,501 patients with AFI were enrolled during March 2020-October 2021;69% underwent SARS-CoV-2 testing. Percentage positivity for SARS-CoV-2 ranged from 4% (87/2,151, Kenya) to 19% (22/115, Ethiopia). We show SARS-CoV-2 testing was successfully integrated into AFI surveillance in 5 low- to middle-income countries to detect COVID-19 within AFI care-seeking populations. AFI surveillance systems can be used to build capacity to detect and respond to both emerging and endemic infectious disease threats.

To assess transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a detention facility experiencing a coronavirus disease outbreak and evaluate testing strategies, we conducted a prospective cohort investigation in a facility in Louisiana, USA. We conducted SARS-CoV-2 testing for detained persons in 6 quarantined dormitories at various time points. Of 143 persons, 53 were positive at the initial test, and an additional 58 persons were positive at later time points (cumulative incidence 78%). In 1 dormitory, all 45 detained persons initially were negative; 18 days later, 40 (89%) were positive. Among persons who were SARS-CoV-2 positive, 47% (52/111) were asymptomatic at the time of specimen collection; 14 had replication-competent virus isolated. Serial SARS-CoV-2 testing might help interrupt transmission through medical isolation and quarantine. Testing in correctional and detention facilities will be most effective when initiated early in an outbreak, inclusive of all exposed persons, and paired with infection prevention and control.

Cryptosporidium is a parasite that causes cryptosporidiosis, a profuse, watery diarrhea that can last up to 3 weeks in immunocompetent patients and can lead to life-threatening malnutrition and wasting in immunocompromised patients.* Fecal-oral transmission can occur by ingestion of contaminated recreational water, drinking water, or food, or through contact with infected persons or animals. For the period 2009-2017, public health officials from 40 states and Puerto Rico voluntarily reported 444 cryptosporidiosis outbreaks resulting in 7,465 cases. Exposure to treated recreational water (e.g., in pools and water playgrounds) was associated with 156 (35.1%) outbreaks resulting in 4,232 (56.7%) cases. Other predominant outbreak exposures included contact with cattle (65 outbreaks; 14.6%) and contact with infected persons in child care settings (57; 12.8%). The annual number of reported cryptosporidiosis outbreaks overall increased an average of approximately 13% per year over time. Reversing this trend will require dissemination of prevention messages to discourage swimming or attending child care while ill with diarrhea and encourage hand washing after contact with animals. Prevention and control measures can be optimized by improving understanding of Cryptosporidium transmission through regular analysis of systematically collected epidemiologic and molecular characterization data.

Background and Objective Community mitigation strategies could help reduce COVID-19 incidence, but there are few studies that explore associations nationally and by urbanicity. In a national county-level analysis, we examined the probability of being identified as a county with rapidly increasing COVID-19 incidence (rapid riser identification) during the summer of 2020 by implementation of mitigation policies prior to the summer, overall and by urbanicity. Methods We analyzed county-level data on rapid riser identification during June 1–September 30, 2020 and statewide closures and statewide mask mandates starting March 19 (obtained from state government websites). Poisson regression models with robust standard error estimation were used to examine differences in the probability of rapid riser identification by implementation of mitigation policies (P-value Results Counties in states that closed for 0–59 days were more likely to become a rapid riser county than those that closed for >59 days, particularly in nonmetropolitan areas. The probability of becoming a rapid riser county was 43% lower among counties that had statewide mask mandates at reopening (adjusted prevalence ratio = 0.57; 95% confidence intervals = 0.51–0.63); when stratified by urbanicity, associations were more pronounced in nonmetropolitan areas. Conclusions These results underscore the potential value of community mitigation strategies in limiting the COVID-19 spread, especially in nonmetropolitan areas.

During early August 2020, county-level incidence of coronavirus disease 2019 (COVID-19) generally decreased across the United States, compared with incidence earlier in the summer (1); however, among young adults aged 18-22 years, incidence increased (2). Increases in incidence among adults aged ≥60 years, who might be more susceptible to severe COVID-19-related illness, have followed increases in younger adults (aged 20-39 years) by an average of 8.7 days (3). Institutions of higher education (colleges and universities) have been identified as settings where incidence among young adults increased during August (4,5). Understanding the extent to which these settings have affected county-level COVID-19 incidence can inform ongoing college and university operations and future planning. To evaluate the effect of large colleges or universities and school instructional format* (remote or in-person) on COVID-19 incidence, start dates and instructional formats for the fall 2020 semester were identified for all not-for-profit large U.S. colleges and universities (≥20,000 total enrolled students). Among counties with large colleges and universities (university counties) included in the analysis, remote-instruction university counties (22) experienced a 17.9% decline in mean COVID-19 incidence during the 21 days before through 21 days after the start of classes (from 17.9 to 14.7 cases per 100,000), and in-person instruction university counties (79) experienced a 56.2% increase in COVID-19 incidence, from 15.3 to 23.9 cases per 100,000. Counties without large colleges and universities (nonuniversity counties) (3,009) experienced a 5.9% decline in COVID-19 incidence, from 15.3 to 14.4 cases per 100,000. Similar findings were observed for percentage of positive test results and hotspot status (i.e., increasing among in-person-instruction university counties). In-person instruction at colleges and universities was associated with increased county-level COVID-19 incidence and percentage test positivity. Implementation of increased mitigation efforts at colleges and universities could minimize on-campus COVID-19 transmission.

Campylobacter jejuni is a leading cause of enteric bacterial illness in the United States. Traditional molecular subtyping methods, such as pulsed-field gel electrophoresis (PFGE) and 7-gene multilocus sequence typing (MLST), provided limited resolution to adequately identify C. jejuni outbreaks and separate out sporadic isolates during outbreak investigations. Whole-genome sequencing (WGS) has emerged as a powerful tool for C. jejuni outbreak detection. In this investigation, 45 human and 11 puppy isolates obtained during a 2016–2018 outbreak linked to pet store puppies were sequenced. Core genome multilocus sequence typing (cgMLST) and high-quality single nucleotide polymorphism (hqSNP) analysis of the sequence data separated the isolates into the same two clades containing minor within-clade differences; however, cgMLST analysis does not require selection of an appropriate reference genome, making the method preferable to hqSNP analysis for Campylobacter surveillance and cluster detection. The isolates were classified as sequence type 2109 (ST2109)—a rarely seen MLST sequence type. PFGE was performed on 38 human and 10 puppy isolates; PFGE patterns did not reliably predict clustering by cgMLST analysis. Genetic detection of antimicrobial resistance determinants predicted that all outbreak-associated isolates would be resistant to six drug classes. Traditional antimicrobial susceptibility testing (AST) confirmed a high correlation between genotypic and phenotypic antimicrobial resistance determinations. WGS analysis linked C. jejuni isolates in humans and pet store puppies even when canine exposure information was unknown, aiding the epidemiological investigation during the outbreak. WGS data were also used to quickly identify the highly drug-resistant profile of these outbreak-associated C. jejuni isolates.

Campylobacter causes an estimated 1.3 million diarrheal illnesses in the United States annually (1). In August 2017, the Florida Department of Health notified CDC of six Campylobacter jejuni infections linked to company A, a national pet store chain based in Ohio. CDC examined whole-genome sequencing (WGS) data and identified six isolates from company A puppies in Florida that were highly related to an isolate from a company A customer in Ohio. This information prompted a multistate investigation by local and state health and agriculture departments and CDC to identify the outbreak source and prevent additional illness. Health officials from six states visited pet stores to collect puppy fecal samples, antibiotic records, and traceback information. Nationally, 118 persons, including 29 pet store employees, in 18 states were identified with illness onset during January 5, 2016-February 4, 2018. In total, six pet store companies were linked to the outbreak. Outbreak isolates were resistant by antibiotic susceptibility testing to all antibiotics commonly used to treat Campylobacter infections, including macrolides and quinolones. Store record reviews revealed that among 149 investigated puppies, 142 (95%) received one or more courses of antibiotics, raising concern that antibiotic use might have led to development of resistance. Public health authorities issued infection prevention recommendations to affected pet stores and recommendations for testing puppies to veterinarians. This outbreak demonstrates that puppies can be a source of multidrug-resistant Campylobacter infections in humans, warranting a closer look at antimicrobial use in the commercial dog industry.

Zoonotic diseases represent critical threats to global health security. Effective mitigation of the impact of endemic and emerging zoonotic diseases of public health importance requires multisectoral collaboration and interdisciplinary partnerships. The US Centers for Disease Control and Prevention created the One Health Zoonotic Disease Prioritization Tool to help countries identify zoonotic diseases of greatest national concern using input from representatives of human health, agriculture, environment, and wildlife sectors. We review 7 One Health Zoonotic Disease Prioritization Tool workshops conducted during 2014–2016, highlighting workshop outcomes, lessons learned, and shared themes from countries implementing this process. We also describe the tool’s ability to help countries focus One Health capacity-building efforts to appropriately prevent, detect, and respond to zoonotic disease threats.