Corrigendum: Fetoplacental transmission and placental response to SARS-CoV-2: evidence from the literature.

[This corrects the article DOI: 10.3389/fmed.2022.

Variation in hospital morbidities in an Australian neonatal intensive care unit network.

Objective: There is an expectation among the public and within the profession that the performance and outcome of neonatal intensive care units (NICUs) should be comparable between centres with a similar setting. This study aims to benchmark and audit performance variation in a regional Australian network of eight NICUs.

Design: Cohort study using prospectively collected data.

Fetoplacental transmission and placental response to SARS-CoV-2: Evidence from the literature.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a dreadful novel coronavirus with global health concerns among pregnant women. To date, the vertical transmission of SARS-CoV-2 during pregnancy remains controversial. We briefly report recent findings of placental response to SARS-CoV-2 infection and updates on vertical transmission.

Bayesian spatial modelling of Ebola outbreaks in Democratic Republic of Congo through the INLA-SPDE approach.

Ebola virus (EBV) disease is a globally acknowledged public health emergency, endemic in the west and equatorial Africa. To understand the epidemiology especially the dynamic pattern of EBV disease, we analyse the EBV case notification data for confirmed cases and reported deaths of the ongoing outbreak in the Democratic Republic of Congo (DRC) between 2018 and 2019, and examined the impact of reported violence on the spread of the virus. Using fully Bayesian geo-statistical analysis through stochastic partial differential equations (SPDE) allows us to quantify the spatial patterns at every point of the spatial domain.

Change in outbreak epicentre and its impact on the importation risks of COVID-19 progression: A modelling study.

Background: The outbreak of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) that was first detected in the city of Wuhan, China has now spread to every inhabitable continent, but now the attention has shifted from China to other epicentres. This study explored early assessment of the influence of spatial proximities and travel patterns from Italy on the further spread of SARS-CoV-2 worldwide.

Methods: Using data on the number of confirmed cases of COVID-19 and air travel data between countries, we applied a stochastic meta-population model to estimate the global spread of COVID-19.

Severe dehydration among cholera patients in Yemen: A cohort profile.

Introduction: Introduction Cholera, an acute diarrheal illness caused by ingestion of food or water contaminated with , is one of the major causes of morbidity and mortality globally. The occurrence of outbreaks of cholera are difficult to prevent in low and middle-income countries, especially those under armed conflicts.

Methods: This study aimed to describe the characteristics of a cohort of inpatients with cholera in two main hospitals in Taiz and Sana'a, Yemen, between 3 February 2017 and 8 December 2017.

Effects of time-lagged meteorological variables on attributable risk of leishmaniasis in central region of Afghanistan.

Background: Leishmaniasis remains one of the world's most neglected vector-borne diseases, affecting predominantly poor communities mainly in developing countries. Previous studies have shown that the distribution and dynamics of leishmaniasis infections are sensitive to environmental factors, however, there are no studies on the burden of leishmaniasis attributable to time-varying meteorological variables.

Methods: This study used data from 3 major leishmaniosis afflicted provinces of Afghanistan, between 2003 and 2009, to provide empirical analysis of change in heat/cold-leishmaniosis association.

Individual and network characteristic associated with hospital-acquired Middle East Respiratory Syndrome coronavirus.

Background: During outbreaks of infectious diseases, transmission of the pathogen can form networks of infected individuals connected either directly or indirectly.

Methods: Network centrality metrics were used to characterize hospital-acquired Middle East Respiratory Syndrome Coronavirus (HA-MERS) outbreaks in the Kingdom of Saudi Arabia between 2012 and 2016. Covariate-adjusted multivariable logistic regression models were applied to assess the effect of individual level risk factors and network level metrics associated with increase in length of hospital stay and risk of deaths from MERS.

Network Analysis of MERS Coronavirus within Households, Communities, and Hospitals to Identify Most Centralized and Super-Spreading in the Arabian Peninsula, 2012 to 2016.

Contact history is crucial during an infectious disease outbreak and vital when seeking to understand and predict the spread of infectious diseases in human populations. The transmission connectivity networks of people infected with highly contagious Middle East respiratory syndrome coronavirus (MERS-CoV) in Saudi Arabia were assessed to identify super-spreading events among the infected patients between 2012 and 2016. Of the 1379 MERS cases recorded during the study period, 321 (23.