Implementation of the 7-1-7 target for detection, notification, and response to public health threats in five countries: a retrospective, observational study.

BACKGROUND: Suboptimal detection and response to recent outbreaks, including COVID-19 and mpox (formerly known as monkeypox), have shown that the world is insufficiently prepared for public health threats. Routine monitoring of detection and response performance of health emergency systems through timeliness metrics has been proposed to evaluate and improve outbreak preparedness and contain health threats early. We implemented 7-1-7 to measure the timeliness of detection (target of ≤7 days from emergence), notification (target of ≤1 day from detection), and completion of seven early response actions (target of ≤7 days from notification), and we identified bottlenecks to and enablers of system performance. METHODS: In this retrospective, observational study, we conducted reviews of public health events in Brazil, Ethiopia, Liberia, Nigeria, and Uganda with staff from ministries of health and national public health institutes. For selected public health events occurring from Jan 1, 2018, to Dec 31, 2022, we calculated timeliness intervals for detection, notification, and early response actions, and synthesised identified bottlenecks and enablers. We mapped bottlenecks and enablers to Joint External Evaluation (second edition) indicators. FINDINGS: Of 41 public health events assessed, 22 (54%) met a target of 7 days to detect (median 6 days [range 0-157]), 29 (71%) met a target of 1 day to notify (0 days [0-24]), and 20 (49%) met a target of 7 days to complete all early response actions (8 days [0-72]). 11 (27%) events met the complete 7-1-7 target, with variation among event types. 25 (61%) of 41 bottlenecks to and 27 (51%) of 53 enablers of detection were at the health facility level, with delays to notification (14 [44%] of 32 bottlenecks) and response (22 [39%] of 56 bottlenecks) most often at an intermediate public health (ie, municipal, district, county, state, or province) level. Rapid resource mobilisation for responses (six [9%] of 65 enablers) from the national level enabled faster responses. INTERPRETATION: The 7-1-7 target is feasible to measure and to achieve, and assessment with this framework can identify areas for performance improvement and help prioritise national planning. Increased investments must be made at the health facility and intermediate public health levels for improved systems to detect, notify, and rapidly respond to emerging public health threats. FUNDING: Bill & Melinda Gates Foundation.

COVID-19 reinfection in Liberia: Implication for improving disease surveillance.

COVID-19 remains a serious disruption to human health, social, and economic existence. Reinfection with the virus intensifies fears and raises more questions among countries, with few documented reports. This study investigated cases of COVID-19 reinfection using patients' laboratory test results between March 2020 and July 2021 in Liberia. Data obtained from Liberia's Ministry of Health COVID-19 surveillance was analyzed in Excel 365 and ArcGIS Pro 2.8.2. Results showed that with a median interval of 200 days (Range: 99-415), 13 out of 5,459 cases were identified and characterized as reinfection in three counties during the country's third wave of the outbreak. Eighty-six percent of the COVID-19 reinfection cases occurred in Montserrado County within high clusters, which accounted for over 80% of the randomly distributed cases in Liberia. More cases of reinfection occurred among international travelers within populations with high community transmissions. This study suggests the need for continued public education and surveillance to encourage longer-term COVID-19 preventive practices even after recovery.

Symptom-based case definitions for COVID-19: Time and geographical variations for detection at hospital admission among 260,000 patients.

Introduction: Case definitions are used to guide clinical practice, surveillance and research protocols. However, how they identify COVID-19-hospitalised patients is not fully understood. We analysed the proportion of hospitalised patients with laboratory-confirmed COVID-19, in the ISARIC prospective cohort study database, meeting widely used case definitions. Methods: Patients were assessed using the Centers for Disease Control (CDC), European Centre for Disease Prevention and Control (ECDC), World Health Organization (WHO) and UK Health Security Agency (UKHSA) case definitions by age, region and time. Case fatality ratios (CFRs) and symptoms of those who did and who did not meet the case definitions were evaluated. Patients with incomplete data and non-laboratory-confirmed test result were excluded. Results: A total of 263,218 of the patients (42%) in the ISARIC database were included. Most patients (90.4%) were from Europe and Central Asia. The proportions of patients meeting the case definitions were 56.8% (WHO), 74.4% (UKHSA), 81.6% (ECDC) and 82.3% (CDC). For each case definition, patients at the extremes of age distribution met the criteria less frequently than those aged 30 to 70 years; geographical and time variations were also observed. Estimated CFRs were similar for the patients who met the case definitions. However, when more patients did not meet the case definition, the CFR increased. Conclusions: The performance of case definitions might be different in different regions and may change over time. Similarly concerning is the fact that older patients often did not meet case definitions, risking delayed medical care. While epidemiologists must balance their analytics with field applicability, ongoing revision of case definitions is necessary to improve patient care through early diagnosis and limit potential nosocomial spread.