Background: Klebsiella pneumoniae (hereafter, Kp) is a major public health threat responsible for high levels of multidrug resistant (MDR) human infections. Besides, Kp also causes severe infections in the community, especially in Asia and Africa. Although most Kp infections are caused by endogenous intestinal carriage, little is known about the prevalence and microbiological characteristics of Kp in asymptomatic human carriage, and attached risk factors including environmental sources exposure. Methods: Here, 911 pregnant women from communities in Madagascar, Cambodia, and Senegal were screened for gut colonization by Kp. Characteristics of Kp strains (antimicrobial susceptibility, genomic diversity, virulence, and resistance genes) were defined, and associated risk factors were investigated. Results: Kp carriage rate was 55.9%, and Kp populations were highly heterogeneous (6 phylogroups, 325 sequence types, Simpson index 99.6%). One third of Kp isolates had acquired antimicrobial resistance genes. MDR-Kp (11.7% to 39.7%) and extended spectrum beta-lactamase (ESBL)-producing Kp (0.7% to 14.7%) varied among countries. Isolates with virulence genes were detected (14.5%). Environmental exposure factors including food, animal contacts, or hospitalization of household members were associated with carriage of Kp, antimicrobial resistance and hypervirulence. However, risk factors were countryspecific and Kp subpopulation-specific. Conclusion: This large-scale multicenter study uncovers the huge diversity of Kp in human gut carriage, demonstrates that antimicrobial resistance is widespread in communities of three lowincome countries, and underlines the challenges posed by Kp colonization to the control of antimicrobial resistance.
Background Long-term care facilities (LTCFs) are vulnerable to outbreaks of coronavirus disease 2019 (COVID-19). Timely epidemiological surveillance is essential for outbreak response, but is complicated by a high proportion of silent (non-symptomatic) infections and limited testing resources. Methods We used a stochastic, individual-based model to simulate transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) along detailed inter-individual contact networks describing patient-staff interactions in a real LTCF setting. We simulated distribution of nasopharyngeal swabs and reverse transcriptase polymerase chain reaction (RT-PCR) tests using clinical and demographic indications and evaluated the efficacy and resource-efficiency of a range of surveillance strategies, including group testing (sample pooling) and testing cascades, which couple (i) testing for multiple indications (symptoms, admission) with (ii) random daily testing. Results In the baseline scenario, randomly introducing a silent SARS-CoV-2 infection into a 170-bed LTCF led to large outbreaks, with a cumulative 86 (95% uncertainty interval 6–224) infections after 3 weeks of unmitigated transmission. Efficacy of symptom-based screening was limited by lags to symptom onset and silent asymptomatic and pre-symptomatic transmission. Across scenarios, testing upon admission detected just 34–66% of patients infected upon LTCF entry, and also missed potential introductions from staff. Random daily testing was more effective when targeting patients than staff, but was overall an inefficient use of limited resources. At high testing capacity (> 10 tests/100 beds/day), cascades were most effective, with a 19–36% probability of detecting outbreaks prior to any nosocomial transmission, and 26–46% prior to first onset of COVID-19 symptoms. Conversely, at low capacity (< 2 tests/100 beds/day), group testing strategies detected outbreaks earliest. Pooling randomly selected patients in a daily group test was most likely to detect outbreaks prior to first symptom onset (16–27%), while pooling patients and staff expressing any COVID-like symptoms was the most efficient means to improve surveillance given resource limitations, compared to the reference requiring only 6–9 additional tests and 11–28 additional swabs to detect outbreaks 1–6 days earlier, prior to an additional 11–22 infections. Conclusions COVID-19 surveillance is challenged by delayed or absent clinical symptoms and imperfect diagnostic sensitivity of standard RT-PCR tests. In our analysis, group testing was the most effective and efficient COVID-19 surveillance strategy for resource-limited LTCFs. Testing cascades were even more effective given ample testing resources. Increasing testing capacity and updating surveillance protocols accordingly could facilitate earlier detection of emerging outbreaks, informing a need for urgent intervention in settings with ongoing nosocomial transmission.
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