Detection of Enterovirus D68 in Wastewater Samples from the UK between July and November 2021

Infection with enterovirus D68 (EV-D68) has been linked with severe neurological disease such as acute flaccid myelitis (AFM) in recent years. However, active surveillance for EV-D68 is lacking, which makes full assessment of this association difficult. Although a high number of EV-D68 infections were expected in 2020 based on the EV-D68′s known biannual circulation patterns, no apparent increase in EV-D68 detections or AFM cases was observed during 2020. We describe an upsurge of EV-D68 detections in wastewater samples from the United Kingdom between July and November 2021 mirroring the recently reported rise in EV-D68 detections in clinical samples from various European countries. We provide the first publicly available 2021 EV-D68 sequences showing co-circulation of EV-D68 strains from genetic clade D and sub-clade B3 as in previous years. Our results show the value of environmental surveillance (ES) for the early detection of circulating and clinically relevant human viruses. The use of a next-generation sequencing (NGS) approach helped us to estimate the prevalence of EV-D68 viruses among EV strains from other EV serotypes and to detect EV-D68 minor variants. The utility of ES at reducing gaps in virus surveillance for EV-D68 and the possible impact of nonpharmaceutical interventions introduced to control the COVID-19 pandemic on EV-D68 transmission dynamics are discussed.

Heterologous vaccination interventions to reduce pandemic morbidity and mortality: Modeling the US winter 2020 COVID-19 wave

COVID-19 remains a stark health threat worldwide, in part because of minimal levels of targeted vaccination outside high-income countries and highly transmissible variants causing infection in vaccinated individuals. Decades of theoretical and experimental data suggest that nonspecific effects of non–COVID-19 vaccines may help bolster population immunological resilience to new pathogens. These routine vaccinations can stimulate heterologous cross-protective effects, which modulate nontargeted infections. For example, immunization with Bacillus Calmette–Guérin, inactivated influenza vaccine, oral polio vaccine, and other vaccines have been associated with some protection from SARS-CoV-2 infection and amelioration of COVID-19 disease. If heterologous vaccine interventions (HVIs) are to be seriously considered by policy makers as bridging or boosting interventions in pandemic settings to augment nonpharmaceutical interventions and specific vaccination efforts, evidence is needed to determine their optimal implementation. Using the COVID-19 International Modeling Consortium mathematical model, we show that logistically realistic HVIs with low (5 to 15%) effectiveness could have reduced COVID-19 cases, hospitalization, and mortality in the United States fall/winter 2020 wave. Similar to other mass drug administration campaigns (e.g., for malaria), HVI impact is highly dependent on both age targeting and intervention timing in relation to incidence, with maximal benefit accruing from implementation across the widest age cohort when the pandemic reproduction number is >1.0. Optimal HVI logistics therefore differ from optimal rollout parameters for specific COVID-19 immunizations. These results may be generalizable beyond COVID-19 and the US to indicate how even minimally effective heterologous immunization campaigns could reduce the burden of future viral pandemics.

The Effectiveness of Governmental Nonpharmaceutical Interventions Against COVID-19 On The Control of Seasonal Influenza Transmission: An Ecological Study

Background: A range of strict nonpharmaceutical interventions (NPIs) had been implemented in many countries to combat the COVID-19 pandemic. These NPIs might also be effective in controlling the seasonal influenza virus, which share the same transmission path with SARS-CoV-2. The aim of this study is to evaluate the effect of different NPIs for control of seasonal influenza.Methods: Data on 14 NPIs implemented in 33 countries and corresponding data on influenza virologic surveillance were collected. The influenza suppression index was calculated as the difference between the influenza-positive rate during its decline period from 2019 to 2020 and that during influenza epidemic seasons in the previous 9 years. A machine learning model was developed by using extreme gradient boosting tree (XGBoost) regressor to fit NPI data and influenza suppression index. SHapley Additive exPlanations (SHAP) was used to characterize NPIs in suppressing influenza.Results: Gathering limitation contributed the most (37.60%) among all NPIs in suppressing influenza transmission in the 2019-2020 influenza season. The top three effective NPIs were gathering limitation, international travel restriction, and school closure. Regarding the three NPIs, their intensity threshold to generate effect were restrictions on the size of gatherings less than 1000 people, travel bans on all regions or total border closure, and closing only some categories of schools, respectively. There was a strong positive interaction effect between mask wearing requirement and gathering limitation, whereas merely implementing mask wearing requirement but ignoring other NPIs would dilute mask wearing requirement’s effectiveness in suppressing influenza.Conclusions: Gathering limitation, travel bans on all regions or total border closure, and closing some levels of schools are the most effective NPIs to suppress influenza transmission. Mask wearing requirement is advised to be combined with gathering limitation and other NPIs. Our findings could facilitate the precise control of future influenza epidemics and potential pandemics.

SARS-CoV-2 transmission dynamics in South Africa and epidemiological characteristics of the Omicron variant

Within days of first detection, Omicron SARS-CoV-2 variant case numbers grew exponentially and spread globally. To better understand variant epidemiological characteristics, we utilize a model-inference system to reconstruct SARS-CoV-2 transmission dynamics in South Africa and decompose novel variant transmissibility and immune erosion. Accounting for under-detection of infection, infection seasonality, nonpharmaceutical interventions, and vaccination, we estimate that the majority of South Africans had been infected by SARS-CoV-2 before the Omicron wave. Based on findings for Gauteng province, Omicron is estimated 100.3% (95% CI: 74.8 - 140.4%) more transmissible than the ancestral SARS-CoV-2 and 36.5% (95% CI: 20.9 - 60.1%) more transmissible than Delta; in addition, Omicron erodes 63.7% (95% CI: 52.9 - 73.9%) of the population immunity, accumulated from prior infections and vaccination, in Gauteng.

Pausing the Pandemic: Understanding and Managing Traveler and Community Spread of COVID-19 in Hawaii

In the absence of a vaccine, nonpharmaceutical interventions such as social distancing and travel reductions were the only strategies for slowing the spread of the COVID-19 pandemic. Using survey data from Hawaii ( n = 22,200) collected in March through May of 2020 at the onset of the pandemic, the differences between traveler spreaders who brought the disease into the state and community spreaders were investigated. In addition to describing the demographic attributes and comparing them with attributes of those who were vulnerable to COVID-19, logit models explaining travel behaviors were developed and tested. Traveler spreaders were likely to be male, younger, and returning students. Community spreaders were more likely to be male, essential workers, first responders, and medical personnel at the highest risk of exposure. Using spatial statistics, clusters and hotspot locations of high-risk individuals were mapped. As transportation researchers are in a position to combine their critical analytical capabilities and experience with relevant databases on mobility and the spread of infectious diseases, this analysis could support efforts to respond to and slow the spread of the pandemic.

Changes in notifiable infectious disease incidence in China during the COVID-19 pandemic

Nationwide nonpharmaceutical interventions (NPIs) have been effective at mitigating the spread of the novel coronavirus disease (COVID-19), but their broad impact on other diseases remains under-investigated. Here we report an ecological analysis comparing the incidence of 31 major notifiable infectious diseases in China in 2020 to the average level during 2014-2019, controlling for temporal phases defined by NPI intensity levels. Respiratory diseases and gastrointestinal or enteroviral diseases declined more than sexually transmitted or bloodborne diseases and vector-borne or zoonotic diseases. Early pandemic phases with more stringent NPIs were associated with greater reductions in disease incidence. Non-respiratory diseases, such as hand, foot and mouth disease, rebounded substantially towards the end of the year 2020 as the NPIs were relaxed. Statistical modeling analyses confirm that strong NPIs were associated with a broad mitigation effect on communicable diseases, but resurgence of non-respiratory diseases should be expected when the NPIs, especially restrictions of human movement and gathering, become less stringent.

The Failures of an Ideal COVID-19 Vaccine: A Simulation Study

This paper simulates an ideal COVID-19 vaccine that confers immediate sterilizing immunity against all SARS-CoV-2 variants. The purpose was to explore how well this ideal vaccine could protect a population against common conditions (such as vaccine hesitancy) that might impair vaccine effectiveness. Simulations were done with an SEIRS spreadsheet model that ran two parallel subpopulations: one that accepted vaccination, and another that refused it. The two subpopulations could transmit infections to one another. Success was judged by the rate of new cases in the period from 1-5 years after the introduction of the vaccine. Under good conditions, including a small subpopulation that refused vaccination, rapid distribution of the vaccine, duration of vaccinal immunity longer than 12 months, good retention of interest in getting vaccinated after the first year, strict maintenance of nonpharmaceutical interventions (NPIs) such as masking, and new variants with R0s less than 4.0, the vaccine was able to end the epidemic. With violation of these conditions, the post-vaccine era futures ranged from endemic COVID at a low or medium level to rates of COVID cases worse than anything seen in the US up to late 2021. The most important conditions for keeping case rates low were a fast speed of vaccine distribution, a low percentage of the population that refuses vaccination, a long duration of vaccinal immunity, and continuing maintenance of NPIs after vaccination began. On the other hand, a short duration of vaccinal immunity, abandonment of NPIs, and new variants with a high R0 were powerful barriers to disease control. New variants with high R0s were particularly damaging, producing high case rates except when vaccination speed was unrealistically rapid. A recurring finding was that most disease afflicting the vaccinated population in these simulations originated in the unvaccinated population, and cutting off interaction with the unvaccinated population caused a sharp drop in the case rate of the vaccinated population. In conclusion, multiple common conditions can compromise the effectiveness of even an ideal vaccine.