Predicting COVID-19 Incidence Using Wastewater Surveillance Data, Denmark, October 2021-June 2022.

Analysis of wastewater is used in many settings for surveillance of SARS-CoV-2, but it remains unclear how well wastewater testing results reflect incidence. Denmark has had an extensive wastewater analysis system that conducts 3 weekly tests in ≈200 sites and has 85% population coverage; the country also offers free SARS-CoV-2 PCR tests to all residents. Using time series analysis for modeling, we found that wastewater data, combined with information on circulating variants and the number of human tests performed, closely fitted the incidence curve of persons testing positive. The results were consistent at a regional level and among a subpopulation of frequently tested healthcare personnel. We used wastewater analysis data to estimate incidence after testing was reduced to a minimum after March 2022. These results imply that data from a large-scale wastewater surveillance system can serve as a good proxy for COVID-19 incidence and for epidemic control.

Comparison of morbidity and mortality after bloodstream infection with vancomycin-resistant versus -susceptible Enterococcus faecium: a nationwide cohort study in Denmark, 2010-2019.

The emergence of bloodstream infections (BSI) caused by vancomycin-resistant Enterococci (VRE) has caused concern. Nonetheless, it remains unclear whether these types are associated with an excess risk of severe outcomes when compared with infections caused by vancomycin-susceptible Enterococci (VSE). This cohort study included hospitalized patients in Denmark with Enterococcus faecium-positive blood cultures collected between 2010 and 2019 identified in the Danish Microbiology Database. We estimated 30-day hazard ratio (HR) of death or discharge among VRE compared to VSE patients adjusted for age, sex, and comorbidity. The cohort included 6071 patients with E. faecium BSI (335 VRE, 5736 VSE) among whom VRE increased (2010-13, 2.6%; 2014-16, 6.3%; 2017-19; 9.4%). Mortality (HR 1.08, 95%CI 0.90-1.29; 126 VRE, 37.6%; 2223 VSE, 37.0%) or discharge (HR 0.89, 95%CI 0.75-1.06; 126 VRE, 37.6%; 2386 VSE, 41.6%) was not different between VRE and VSE except in 2014 (HR 1.87, 95% CI 1.18-2.96). There was no interaction between time from admission to BSI (1-2, 3-14, and >14 days) and HR of death (P = 0.14) or discharge (P = 0.45) after VRE compared to VSE, despite longer time for VRE patients (17 vs. 10 days for VSE, P < 0.0001). In conclusion, VRE BSI was not associated with excess morbidity and mortality. The excess mortality in 2014 only may be attributed to improved diagnostic- and patient-management practices after 2014, reducing time to appropriate antibiotic therapy. The high level of mortality after E. faecium BSI warrants further study.

Cholera hotspots and surveillance constraints contributing to recurrent epidemics in Tanzania.

OBJECTIVE: We described the dynamics of cholera in Tanzania between 2007 and 2017 and assessed the weaknesses of the current surveillance system in providing necessary data in achieving the global roadmap to 2030 for cholera control. RESULTS: The Poisson-based spatial scan identified cholera hotspots in mainland Tanzania. A zero-inflated Poisson regression investigated the relationship between the incidence of cholera and available demographic, socio-economic and climatic exposure variables. Four cholera hotspots were detected covering 17 regions, home to 28 million people, including the central regions and those surrounding the Lakes Victoria, Tanganyika and Nyaza. The risk of experiencing cholera in these regions was up to 2.9 times higher than elsewhere in the country. Regression analyses revealed that every 100 km of water perimeter in a region increased the cholera incidence by 1.5%. Due to the compilation of surveillance data at regional level rather than at district, we were unable to reliably identify any other significant risk factors and specific hotspots. Cholera high-risk populations in Tanzania include those living near lakes and central regions. Successful surveillance require disaggregated data available weekly and at district levels in order to serve as data for action to support the roadmap for cholera control.