Latino Household Transmission of Severe Acute Respiratory Syndrome Coronavirus 2.

We assessed temporal changes in the household secondary attack rate of severe acute respiratory syndrome coronavirus 2 and identified risk factors for transmission in vulnerable Latino households of Baltimore, Maryland. The household secondary attack rate was 45.8%, and it appeared to increase as the alpha variant spread, highlighting the magnified risk of spread in unvaccinated populations.

Teleconsultation for outpatient care of patients during the Covid-19 pandemic at a University Hospital in Colombia.

BACKGROUND: During the COVID 19 pandemic, direct-to-consumer telehealth (DTC) services allowed patients real-time virtual access to healthcare providers, especially those with an established relationship. In Colombia, this care modality was implemented between 2019 and 2020, under national considerations, it was implemented for outpatient care in a highly complex university hospital in Cali, Colombia. METHODS: A descriptive study with prospective information collection was used to describe the implementation of the outpatient teleconsultation care model for patients. We constructed the clinical and process indicators with which we evaluated the model. FINDINGS: A total of 56,560 patients from our institution were treated by virtual outpatient consultation during the first nine months of the health emergency declared by COVID 19 in Colombia. The strategy made it possible to achieve coverage more significant than 100% in Cali and the departments of Colombia. Attention by teleconsultation was 19% of the total ambulatory care. The effectiveness in carrying out scheduled teleconsultations had an overall result of 91.5%. The accessibility results demonstrated the need to strengthen connectivity and accessibility to payments and strengthen technology adoption in the institution, health personnel, and patients. INTERPRETATION: Implementing an outpatient teleconsultation model allowed the continuity of the management with comprehensive coverage nationwide from a highly complex hospital in southwestern Colombia. The indicators' analysis should help strengthen the policies of access to telemedicine, especially with the consequences of the pandemic in low- and middle-income countries. Latin American evidence is necessary to establish the safety profile of telemedicine and the costs associated with the provision.

Pregnancy and pandemics: Interaction of viral surface proteins and placenta cells.

Throughout history, pandemics of infectious diseases caused by emerging viruses have spread worldwide. Evidence from previous outbreaks demonstrated that pregnant women are at high risk of contracting the diseases and suffering from adverse outcomes. However, while some viruses can cause major health complications for the mother and her fetus, others do not appear to affect pregnancy. Viral surface proteins bind to specific receptors on the cellular membrane of host cells and begin therewith the infection process. During pregnancy, the molecular features of these proteins may determine specific target cells in the placenta, which may explain the different outcomes. In this review, we display information on Variola, Influenza, Zika and Corona viruses focused on their surface proteins, effects on pregnancy, and possible target placental cells. This will contribute to understanding viral entry during pregnancy, as well as to develop strategies to decrease the incidence of obstetrical problems in current and future infections.

Accuracy of State-Level Surveillance during Emerging Outbreaks of Respiratory Viruses: A Model-Based Assessment.

It is long perceived that the more data collection, the more knowledge emerges about the real disease progression. During emergencies like the H1N1 and the severe acute respiratory syndrome coronavirus 2 pandemics, public health surveillance requested increased testing to address the exacerbated demand. However, it is currently unknown how accurately surveillance portrays disease progression through incidence and confirmed case trends. State surveillance, unlike commercial testing, can process specimens based on the upcoming demand (e.g., with testing restrictions). Hence, proper assessment of accuracy may lead to improvements for a robust infrastructure. Using the H1N1 pandemic experience, we developed a simulation that models the true unobserved influenza incidence trend in the State of Michigan, as well as trends observed at different data collection points of the surveillance system. We calculated the growth rate, or speed at which each trend increases during the pandemic growth phase, and we performed statistical experiments to assess the biases (or differences) between growth rates of unobserved and observed trends. We highlight the following results: 1) emergency-driven high-risk perception increases reporting, which leads to reduction of biases in the growth rates; 2) the best predicted growth rates are those estimated from the trend of specimens submitted to the surveillance point that receives reports from a variety of health care providers; and 3) under several criteria to queue specimens for viral subtyping with limited capacity, the best-performing criterion was to queue first-come, first-serve restricted to specimens with higher hospitalization risk. Under this criterion, the lab released capacity to subtype specimens for each day in the trend, which reduced the growth rate bias the most compared to other queuing criteria. Future research should investigate additional restrictions to the queue.