Chlamydia trachomatis, Neisseria gonorrhoea, and Trichomonas vaginalis infections among pregnant women and male partners in Dutch midwifery practices: prevalence, risk factors, and perinatal outcomes.

Background: Antenatal screening for HIV, syphilis and HBV has been successfully implemented in The Netherlands, but data on other STI among pregnant women or male partners are limited. Our objectives: (i) to assess the prevalence of Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG) and Trichomonas vaginalis (TV) among pregnant women and male partners, (ii) to identify risk factors for these STI during pregnancy, and (iii) to identify adverse perinatal outcomes (APO) associated with STI.

Methods: Cross-sectional study.

Model of care, Noma Children's Hospital, northwest Nigeria.

The Nigerian Ministry of Health has been offering care for noma patients for many years at the Noma Children's Hospital (NCH) in Sokoto, northwest Nigeria, and Médecins Sans Frontières has supported these initiatives since 2014. The comprehensive model of care consists of four main components: acute care, care for noma sequelae, integrated hospital-based services and community-based services. The model of care is based on the limited evidence available for prevention and treatment of noma and follows WHO's protocols for acute patients and best practice guidelines for the surgical treatment of noma survivors.

Utility of whole-genome sequencing during an investigation of multiple foodborne outbreaks of .

In April 2018, Public Health England was notified of cases of Shigella sonnei who had eaten food from three different catering outlets in England. The outbreaks were initially investigated as separate events, but whole-genome sequencing (WGS) showed they were caused by the same strain. The investigation included analyses of epidemiological data, the food chain and microbiological examination of food samples.

The effect of medication related clinical decision support at the time of physician order entry.

Background In advanced clinical decision support systems, patient characteristics and laboratory values are included in the algorithms that generate alerts. These alerts have a higher specificity than basic medication surveillance alerts. The alerts of advanced clinical decision support systems can be shown directly to the prescriber during order entry, without the risk of generating an overload of irrelevant alerts.