On alert for Ebola: public health risk assessment of travellers from Uganda to the USA during the 2022 outbreak.

BACKGROUND: On 20 September 2022, the Ugandan Ministry of Health declared an outbreak of Ebola disease caused by Sudan ebolavirus. METHODS: From 6 October 2022 to 10 January 2023, Centers for Disease Control and Prevention (CDC) staff conducted public health assessments at five US ports of entry for travellers identified as having been in Uganda in the past 21 days. CDC also recommended that state, local and territorial health departments ('health departments') conduct post-arrival monitoring of these travellers. CDC provided traveller contact information, daily to 58 health departments, and collected health department data regarding monitoring outcomes. RESULTS: Among 11 583 travellers screened, 132 (1%) required additional assessment due to potential exposures or symptoms of concern. Fifty-three (91%) health departments reported receiving traveller data from CDC for 10 114 (87%) travellers, of whom 8499 (84%) were contacted for monitoring, 1547 (15%) could not be contacted and 68 (1%) had no reported outcomes. No travellers with high-risk exposures or Ebola disease were identified. CONCLUSION: Entry risk assessment and post-arrival monitoring of travellers are resource-intensive activities that had low demonstrated yield during this and previous outbreaks. The efficiency of future responses could be improved by incorporating an assessment of risk of importation of disease, accounting for individual travellers' potential for exposure, and expanded use of methods that reduce burden to federal agencies, health departments, and travellers.

Early introductions and transmission of SARS-CoV-2 variant B.1.1.7 in the United States.

The emergence and spread of SARS-CoV-2 lineage B.1.1.7, first detected in the United Kingdom, has become a global public health concern because of its increased transmissibility. Over 2,500 COVID-19 cases associated with this variant have been detected in the United States (US) since December 2020, but the extent of establishment is relatively unknown. Using travel, genomic, and diagnostic data, we highlight that the primary ports of entry for B.1.1.7 in the US were in New York, California, and Florida. Furthermore, we found evidence for many independent B.1.1.7 establishments starting in early December 2020, followed by interstate spread by the end of the month. Finally, we project that B.1.1.7 will be the dominant lineage in many states by mid- to late March. Thus, genomic surveillance for B.1.1.7 and other variants urgently needs to be enhanced to better inform the public health response.

Early introductions and community transmission of SARS-CoV-2 variant B.1.1.7 in the United States.

The emergence and spread of SARS-CoV-2 lineage B.1.1.7, first detected in the United Kingdom, has become a global public health concern because of its increased transmissibility. Over 2500 COVID-19 cases associated with this variant have been detected in the US since December 2020, but the extent of establishment is relatively unknown. Using travel, genomic, and diagnostic data, we highlight the primary ports of entry for B.1.1.7 in the US and locations of possible underreporting of B.1.1.7 cases. Furthermore, we found evidence for many independent B.1.1.7 establishments starting in early December 2020, followed by interstate spread by the end of the month. Finally, we project that B.1.1.7 will be the dominant lineage in many states by mid to late March. Thus, genomic surveillance for B.1.1.7 and other variants urgently needs to be enhanced to better inform the public health response.

Quinolone nonsusceptibility among enteric pathogens isolated from international travelers - Foodborne Diseases Active Surveillance Network (FoodNet) and National Antimicrobial Monitoring System (NARMS), 10 United States sites, 2004 - 2014.

Gastrointestinal illnesses are the most frequently diagnosed conditions among returning U.S. travelers. Although most episodes of travelers' diarrhea do not require antibiotic therapy, fluoroquinolones (a type of quinolone antibiotic) are recommended for treatment of moderate and severe travelers' diarrhea as well as many other types of severe infection. To assess associations between quinolone susceptibility and international travel, we linked data about isolate susceptibility in NARMS to cases of enteric infections reported to FoodNet. We categorized isolates as quinolone-nonsusceptible (QNS) if they were resistant or had intermediate susceptibility to ≥1 quinolone. Among 1,726 travel-associated infections reported to FoodNet with antimicrobial susceptibility data in NARMS during 2004-2014, 56% of isolates were quinolone-nonsusceptible, of which most (904/960) were Campylobacter. International travel was associated with >10-fold increased odds of infection with quinolone-nonsusceptible bacteria. Most QNS infections were associated with travel to Latin America and the Caribbean (390/743; 52%); however, the greatest risk of QNS infection was associated with travel to Africa (120 per 1,000,000 passenger journeys). Preventing acquisition and onward transmission of antimicrobial-resistant enteric infections among travelers is critical.

Mining the literature for genes associated with placenta-mediated maternal diseases.

Automated literature analysis could significantly speed up understanding of the role of the placenta and the impact of its development and functions on the health of the mother and the child. To facilitate automatic extraction of information about placenta-mediated disorders from the literature, we manually annotated genes and proteins, the associated diseases, and the functions and processes involved in the development and function of placenta in a collection of PubMed/MEDLINE abstracts. We developed three baseline approaches to finding sentences containing this information: one based on supervised machine learning (ML) and two based on distant supervision: 1) using automated detection of named entities and 2) using MeSH. We compare the performance of several well-known supervised ML algorithms and identify two approaches, Support Vector Machines (SVM) and Generalized Linear Models (GLM), which yield up to 98% recall precision and F1 score. We demonstrate that distant supervision approaches could be used at the expense of missing up to 15% of relevant documents.

Evaluation of methicillin-resistant Staphylococcus aureus skin and soft-tissue infection prevention strategies at a military training center.

Military trainees are at high risk for skin and soft-tissue infections (SSTIs), especially those caused by methicillin-resistant Staphylococcus aureus (MRSA). A multicomponent hygiene-based SSTI prevention strategy was implemented at a military training center. After implementation, we observed 30% and 64% reductions in overall and MRSA-associated SSTI rates, respectively.