Etiology of Acute Febrile Illness in the Peruvian Amazon as determined by modular formatted quantitative PCR: A Protocol for RIVERA, a Health Facility-Based Case-Control Study.

Background : The study of the etiology of acute febrile illness (AFI) has historically been designed as a prevalence of pathogens detected from a case series. This strategy has an inherent unrealistic assumption that all pathogen detection allows for causal attribution, despite known asymptomatic carriage of the principal causes of acute febrile illness in most low- and middle-income countries (LMICs). We designed a semi-quantitative PCR in a modular format to detect bloodborne agents of acute febrile illness that encompassed common etiologies of AFI in the region, etiologies of recent epidemics, etiologies that require an immediate public health response and additional pathogens of unknown endemicity. We then designed a study that would delineate background levels of transmission in the community in the absence of symptoms to provide corrected estimates of attribution for the principal determinants of AFI. Methods : A case-control study of acute febrile illness in patients ten years or older seeking health care in Iquitos, Loreto, Peru, was planned. Upon enrollment, we will obtain blood, saliva, and mid-turbinate nasal swabs at enrollment with a follow-up visit on day 21-28 following enrollment to attain vital status and convalescent saliva and blood samples, as well as a questionnaire including clinical, socio-demographic, occupational, travel, and animal contact information for each participant. Whole blood samples are to be simultaneously tested for 32 pathogens using TaqMan array cards. Mid-turbinate samples will be tested for SARS-CoV-2, Influenza A and Influenza B. Conditional logistic regression models will be fitted treating case/control status as the outcome and with pathogen-specific sample positivity as predictors to attain estimates of attributable pathogen fractions for AFI. Discussion : The modular PCR platforms will allow for reporting of all primary results of respiratory samples within 72 hours and blood samples within one week, allowing for results to influence local medical practice and enable timely public health responses. The inclusion of controls will allow for a more accurate estimate of the importance of specific, prevalent pathogens as a cause of acute illness. Study Registration: Project 1791, Registro de Proyectos de Investigación en Salud Pública (PRISA), Instituto Nacional de Salud, Perú.

Etiology of acute febrile illness in the peruvian amazon as determined by modular formatted quantitative PCR: a protocol for RIVERA, a health facility-based case-control study.

BACKGROUND: The study of the etiology of acute febrile illness (AFI) has historically been designed as a prevalence of pathogens detected from a case series. This strategy has an inherent unrealistic assumption that all pathogen detection allows for causal attribution, despite known asymptomatic carriage of the principal causes of acute febrile illness in most low- and middle-income countries (LMICs). We designed a semi-quantitative PCR in a modular format to detect bloodborne agents of acute febrile illness that encompassed common etiologies of AFI in the region, etiologies of recent epidemics, etiologies that require an immediate public health response and additional pathogens of unknown endemicity. We then designed a study that would delineate background levels of transmission in the community in the absence of symptoms to provide corrected estimates of attribution for the principal determinants of AFI. METHODS: A case-control study of acute febrile illness in patients ten years or older seeking health care in Iquitos, Loreto, Peru, was planned. Upon enrollment, we will obtain blood, saliva, and mid-turbinate nasal swabs at enrollment with a follow-up visit on day 21-28 following enrollment to attain vital status and convalescent saliva and blood samples, as well as a questionnaire including clinical, socio-demographic, occupational, travel, and animal contact information for each participant. Whole blood samples are to be simultaneously tested for 32 pathogens using TaqMan array cards. Mid-turbinate samples will be tested for SARS-CoV-2, Influenza A and Influenza B. Conditional logistic regression models will be fitted treating case/control status as the outcome and with pathogen-specific sample positivity as predictors to attain estimates of attributable pathogen fractions for AFI. DISCUSSION: The modular PCR platforms will allow for reporting of all primary results of respiratory samples within 72 h and blood samples within one week, allowing for results to influence local medical practice and enable timely public health responses. The inclusion of controls will allow for a more accurate estimate of the importance of specific prevalent pathogens as a cause of acute illness. STUDY REGISTRATION: Project 1791, Registro de Proyectos de Investigación en Salud Pública (PRISA), Instituto Nacional de Salud, Perú.

Incorporating COVID-19 into Acute Febrile Illness Surveillance Systems, Belize, Kenya, Ethiopia, Peru, and Liberia, 2020-2021.

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.

Opening of Large Institutions of Higher Education and County-Level COVID-19 Incidence - United States, July 6-September 17, 2020.

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.

Differences in rapid increases in county-level COVID-19 incidence by implementation of statewide closures and mask mandates - United States, June 1-September 30, 2020.

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< .05); associations were adjusted for county population size. 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.

Rapid Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 in Detention Facility, Louisiana, USA, May-June, 2020.

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.

Identification of Presymptomatic and Asymptomatic Cases Using Cohort-Based Testing Approaches at a Large Correctional Facility-Chicago, Illinois, USA, May 2020.

BACKGROUND: Coronavirus disease 2019 (COVID-19) continues to cause significant morbidity and mortality worldwide. Correctional and detention facilities are at high risk of experiencing outbreaks. We aimed to evaluate cohort-based testing among detained persons exposed to laboratory-confirmed cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in order to identify presymptomatic and asymptomatic cases. METHODS: During 1-19 May 2020, 2 testing strategies were implemented in 12 tiers or housing units of the Cook County Jail, Chicago, Illinois. Detained persons were approached to participate in serial testing (n = 137) and offered tests at 3 time points over 14 days (day 1, days 3-5, and days 13-14). The second group was offered a single test and interview at the end of a 14-day quarantine period (day 14 group) (n = 87). RESULTS: 224 detained persons were approached for participation and, of these, 194 (87%) participated in ≥1 interview and 172 (77%) had ≥1 test. Of the 172 tested, 19 were positive for SARS-CoV-2. In the serial testing group, 17 (89%) new cases were detected, 16 (84%) on day 1, 1 (5%) on days 3-5, and none on days 13-14; in the day 14 group, 2 (11%) cases were identified. More than half (12/19; 63%) of the newly identified cases were presymptomatic or asymptomatic. CONCLUSIONS: Our findings highlight the utility of cohort-based testing promptly after initiating quarantine within a housing tier. Cohort-based testing efforts identified new SARS-CoV-2 asymptomatic and presymptomatic infections that may have been missed by symptom screening alone.