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Significance Confronted with escalating COVID-19 outbreaks, countries at the leading edge of the pandemic have had to resort to imposing drastic social distancing measures which have serious societal and economic repercussions. Establishing herd immunity in a population by allowing the epidemic to spread, while mitigating the negative health impacts of COVID-19, presents a tantalizing resolution to the crisis. Our study simulating SARS-CoV-2 spread in the United Kingdom finds that achieving herd immunity without overwhelming hospital capacity leaves little room for error. Intervention levels must be carefully manipulated in an adaptive manner for an extended period, despite acute sensitivity to poorly quantified epidemiological factors. Such fine-tuning of social distancing renders this strategy impractical., The rapid growth rate of COVID-19 continues to threaten to overwhelm healthcare systems in multiple countries. In response, severely affected countries have had to impose a range of public health strategies achieved via nonpharmaceutical interventions. Broadly, these strategies have fallen into two categories: 1) “mitigation,” which aims to achieve herd immunity by allowing the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus to spread through the population while mitigating disease burden, and 2) “suppression,” aiming to drastically reduce SARS-CoV-2 transmission rates and halt endogenous transmission in the target population. Using an age-structured transmission model, parameterized to simulate SARS-CoV-2 transmission in the United Kingdom, we assessed the long-term prospects of success using both of these approaches. We simulated a range of different nonpharmaceutical intervention scenarios incorporating social distancing applied to differing age groups. Our modeling confirmed that suppression of SARS-CoV-2 transmission is possible with plausible levels of social distancing over a period of months, consistent with observed trends. Notably, our modeling did not support achieving herd immunity as a practical objective, requiring an unlikely balancing of multiple poorly defined forces. Specifically, we found that 1) social distancing must initially reduce the transmission rate to within a narrow range, 2) to compensate for susceptible depletion, the extent of social distancing must be adaptive over time in a precise yet unfeasible way, and 3) social distancing must be maintained for an extended period to ensure the healthcare system is not overwhelmed.

Timely forecasts of the emergence, re-emergence and elimination of human infectious diseases allow for proactive, rather than reactive, decisions that save lives. Recent theory suggests that a generic feature of dynamical systems approaching a tipping point—early warning signals (EWS) due to critical slowing down (CSD)—can anticipate disease emergence and elimination. Empirical studies documenting CSD in observed disease dynamics are scarce, but such demonstration of concept is essential to the further development of model-independent outbreak detection systems. Here, we use fitted, mechanistic models of measles transmission in four cities in Niger to detect CSD through statistical EWS. We find that several EWS accurately anticipate measles re-emergence and elimination, suggesting that CSD should be detectable before disease transmission systems cross key tipping points. These findings support the idea that statistical signals based on CSD, coupled with decision-support algorithms and expert judgement, could provide the basis for early warning systems of disease outbreaks.

Model structures and supplementary figures.

Inflammatory bowel disease (IBD) with very early onset manifestations (younger than six years of age) is an essential pediatric gastrointestinal disease that encompasses a group of diverse and rare genetic defects. It may be associated with chronicity, premalignant nature, and high morbidity and mortality during childhood. Because of overlapping phenotypes, the definitive diagnosis based on conventional strategies is frequently a challenge. However, many patients with different molecular pathologies are treated with the same therapeutic strategy. In this context, it is essential to define a more reliable method to provide an opportunity for a rapid and accurate diagnosis. Here we report a novel homozygous exonic variant in a patient with an IBD-like lesion in the colon during the infancy period. A 7 months old boy who was born of a consanguineous marriage developed gastrointestinal disorders early in life. After complete diagnostic workups, this case underwent conventional therapy of IBD for five months; but clinical remission was not achieved. We identified a novel homozygous mutation (c.684C > T p(=)) in exon 7 of IL-12RB1 gene that in silico studies indicated its significance in the splicing process. At the 14th month of age, this case died. Our finding reveals the importance of genetic screening as an early diagnostic tool in the identification of the underlying causes of IBD with very early onset manifestations, particularly infantile ( < 2 years of age) IBD. This strategy makes an opportunity in prompt diagnosis and targeted therapy.

Initial efforts to mitigate transmission of SARS-CoV-2 relied on intensive social distancing measures such as school and workplace closures, shelter-in-place orders and prohibitions on the gathering of people. Other non-pharmaceutical interventions for suppressing transmission include active case finding, contact tracing, quarantine, immunity or health certification, and a wide range of personal protective measures. Here we investigate the potential effectiveness of these alternative approaches to suppression. We introduce a conceptual framework represented by two mathematical models that differ in strategy. We find both strategies may be effective, although both require extensive testing and work within a relatively narrow range of conditions. Generalized protective measures such as wearing face masks, improved hygiene and local reductions in density are found to significantly increase the effectiveness of targeted interventions.

Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) is responsible for the outbreak of a new viral respiratory infection. It has been demonstrated that the microbiota has a crucial role in establishing immune responses against respiratory infections, which are controlled by a bidirectional cross-talk, known as the “gut-lung axis.” The effects of microbiota on antiviral immune responses, including dendritic cell (DC) function and lymphocyte homing in the gut-lung axis, have been reported in the recent literature. Additionally, the gut microbiota composition affects (and is affected by) the expression of angiotensin-converting enzyme-2 (ACE2), which is the main receptor for SARS-CoV-2 and contributes to regulate inflammation. Several studies demonstrated an altered microbiota composition in patients infected with SARS-CoV-2, compared to healthy individuals. Furthermore, it has been shown that vaccine efficacy against viral respiratory infection is influenced by probiotics pretreatment. Therefore, the importance of the gut microbiota composition in the lung immune system and ACE2 expression could be valuable to provide optimal therapeutic approaches for SARS-CoV-2 and to preserve the symbiotic relationship of the microbiota with the host.