SARS-CoV-2 lineage B.6 was the major contributor to early pandemic transmission in Malaysia

Malaysia had 10,219 confirmed cases of COVID-19 as of September 20, 2020. About 33% were associated with a Tablighi Jamaat religious mass gathering held in Kuala Lumpur between February 27 and March 3, 2020, which drove community transmission during Malaysia’s second wave. We analysed genome sequences of SARS-CoV-2 from Malaysia to better understand the molecular epidemiology and spread. We obtained 58 SARS-CoV-2 whole genome sequences from patients in Kuala Lumpur and performed phylogenetic analyses on these and a further 57 Malaysian sequences available in the GISAID database. Nine different SARS-CoV-2 lineages (A, B, B.1, B.1.1, B.1.1.1, B.1.36, B.2, B.3 and B.6) were detected in Malaysia. The B.6 lineage was first reported a week after the Tablighi mass gathering and became predominant (65.2%) despite being relatively rare (1.4%) globally. Direct epidemiological links between lineage B.6 viruses and the mass gathering were identified. Increases in reported total cases, Tablighi-associated cases, and community-acquired B.6 lineage strains were temporally linked. Non-B.6 lineages were mainly travel-associated and showed limited onward transmission. There were also temporally correlated increases in B.6 sequences in other Southeast Asian countries, India and Australia, linked to participants returning from this event. Over 95% of global B.6 sequences originated from Asia Pacific. We also report a nsp3-C6310A substitution found in 47.3% of global B.6 sequences which was associated with reduced sensitivity using a commercial diagnostic real-time PCR assay. Lineage B.6 became the predominant cause of community transmission in Malaysia after likely introduction during a religious mass gathering. This event also contributed to spikes of lineage B.6 in other countries in the Asia-Pacific. Mass gatherings can be significant causes of local and global spread of COVID-19. Shared genomic surveillance can be used to identify SARS-CoV-2 transmission chains to aid prevention and control, and to monitor diagnostic molecular assays.Clinical Trial Registration: COVID-19 paper.     

Repercussions of the COVID-19 pandemic on athletes: a cross-sectional study

The COVID-19 pandemic has presented significant challenges and implications for the sports community. Thus, this study aimed to describe the prevalence of COVID-19 in Brazilian athletes and identify the epidemiological, clinical, athletic, life and health factors associated with the disease in these individuals. A cross-sectional study was performed involving 414 athletes from 22 different sports using an online questionnaire from August to November 2020. The association between the athletes’ characteristics and COVID-19 was evaluated using a logistic regression model. The prevalence of COVID-19 was 8.5%, although only 40% of athletes reported having been tested. Being under 27 years of age (3-fold), having children (~5-fold), having a teammate test positive for COVID-19 (2.5-fold), and smoking (14-fold) were associated with a possible higher risk of disease. Almost 20% of athletes self-reported musculoskeletal injuries during the period of the pandemic that was studied. Athletes with a university education (P = 0.02), a profession other than sports (P < 0.001), those from a low-income family (P = 0.01), and public health system users (P = 0.04) were significantly less frequently tested for COVID-19, whereas international competitors, athletes who received a wage, and athletes who had a teammate who tested positive for COVID-19 were 2-, 3-, and 15-fold more likely to be tested for COVID-19, respectively. Approximately 26% of the athletes who tested negative or were untested reported more than three characteristic COVID-19 symptoms, and 11% of athletes who tested positive for COVID-19 were asymptomatic. The identification of modifiable (have children, smoking, and teammates positively tested) and non-modifiable (age under 27 years) factors related to COVID-19 in athletes can contribute to implementing surveillance programmes to decrease the incidence of COVID-19 in athletes and its negative impacts in sports.     

Inferring the effective reproductive number from deterministic and semi-deterministic compartmental models using incidence and mobility data

The effective reproduction number (ℜ_t) is a theoretical indicator of the course of an infectious disease that allows policymakers to evaluate whether current or previous control efforts have been successful or whether additional interventions are necessary. This metric, however, cannot be directly observed and must be inferred from available data. One approach to obtaining such estimates is fitting compartmental models to incidence data. We can envision these dynamic models as the ensemble of structures that describe the disease’s natural history and individuals’ behavioural patterns. In the context of the response to the COVID-19 pandemic, the assumption of a constant transmission rate is rendered unrealistic, and it is critical to identify a mathematical formulation that accounts for changes in contact patterns. In this work, we leverage existing approaches to propose three complementary formulations that yield similar estimates for ℜ_t based on data from Ireland’s first COVID-19 wave. We describe these Data Generating Processes (DGP) in terms of State-Space models. Two (DGP1 and DGP2) correspond to stochastic process models whose transmission rate is modelled as Brownian motion processes (Geometric and Cox-Ingersoll-Ross). These DGPs share a measurement model that accounts for incidence and transmission rates, where mobility data is assumed as a proxy of the transmission rate. We perform inference on these structures using Iterated Filtering and the Particle Filter. The final DGP (DGP3) is built from a pool of deterministic models that describe the transmission rate as information delays. We calibrate this pool of models to incidence reports using Hamiltonian Monte Carlo. By following this complementary approach, we assess the tradeoffs associated with each formulation and reflect on the benefits/risks of incorporating proxy data into the inference process. We anticipate this work will help evaluate the implications of choosing a particular formulation for the dynamics and observation of the time-varying transmission rate.     

Staff Scientist Perspectives on Onboarding and Professional Development: A Case Study

Across the United States, the number of staff scientists (master’s- or doctoral-level professionals working in nonfaculty roles) has grown by 35% since 2010, and they play an increasingly important role in research efforts. However, few targeted resources are available, which potentially limits the effectiveness of this group. Launched in 2016, the staff scientist path at Emory has tripled in size over 4 y to 138 staff. The present case study evaluated the perceptions of staff scientists related to onboarding experiences and professional development needs, including those needs arising from coronavirus disease 2019 (COVID-19) impacts in the workplace. A survey of Emory staff scientists was conducted from May to June 2019 as part of a program evaluation initiative to assess perceptions of onboarding and professional development opportunities. Interviews with a subset of scientists informed the survey development and identified COVID-19–related impacts on daily work. Results indicated the need for targeted orientation resources specific to staff scientists, accurate and timely information and resources to support scientists’ supervisors, and professional development for scientists in leadership and management-related skills. Remote work associated with COVID-19 accentuated the need for managerial skills, including team development in digital work environments. Findings from this case study can inform policies and practices at Emory and other institutions that employ a similar staff scientist model.     

Malaria,COVID-19 and angiotensin-converting enzyme 2: what does the available population data say?

The etiopathogenesis of COVID-19 and its differential geographic spread suggest some populations are apparently ‘less affected’ through many host-related factors that involve angiotensin-converting enzyme 2 (ACE2) protein, which is also the entry receptor for SARS-CoV-2. The role of ACE2 has been well studied in COVID-19 but not in the context of malaria and COVID-19. We have previously suggested how malaria might intersect with COVID-19 through ACE2 mutation and here we evaluate the currently available data that could provide a link between the two diseases. Based on the existing global and Indian data on malaria, COVID-19 and the suggested ACE2 mutation, the association could not be examined robustly, neither accepting nor refuting the suggested hypothesis. We strongly recommend targeted evaluation of this hypothesis through carefully designed robust molecular epidemiological studies.     

Clinical and Genetic Characteristics of Coronaviruses with Particular Emphasis on SARS-CoV-2 Virus

The rapidly spreading Coronavirus Disease 2019 (COVID-19) pandemic has led to a global health crisis and has left a deep mark on society, culture, and the global economy. Despite considerable efforts made to contain the disease, SARS-CoV-2 still poses a threat on a global scale. The current epidemiological situation caused an urgent need to understand the basic mechanisms of the virus transmission and COVID-19 severe course. This review summarizes current knowledge on clinical courses, diagnostics, treatment, and prevention of COVID-19. Moreover, we have included the latest research results on the genetic characterization of SARS-CoV-2 and genetic determinants of susceptibility and severity to infection.     

An integrated framework for building trustworthy data-driven epidemiological models: Application to the COVID-19 outbreak in New York City

Epidemiological models can provide the dynamic evolution of a pandemic but they are based on many assumptions and parameters that have to be adjusted over the time the pandemic lasts. However, often the available data are not sufficient to identify the model parameters and hence infer the unobserved dynamics. Here, we develop a general framework for building a trustworthy data-driven epidemiological model, consisting of a workflow that integrates data acquisition and event timeline, model development, identifiability analysis, sensitivity analysis, model calibration, model robustness analysis, and projection with uncertainties in different scenarios. In particular, we apply this framework to propose a modified susceptible–exposed–infectious–recovered (SEIR) model, including new compartments and model vaccination in order to project the transmission dynamics of COVID-19 in New York City (NYC). We find that we can uniquely estimate the model parameters and accurately project the daily new infection cases, hospitalizations, and deaths, in agreement with the available data from NYC’s government’s website. In addition, we employ the calibrated data-driven model to study the effects of vaccination and timing of reopening indoor dining in NYC.     

Beyond Lassa Fever: Systemic and structural barriers to disease detection and response in Sierra Leone

BackgroundLassa fever (LF) often presents clinically as undifferentiated febrile illness. Lassa Fever cases in Sierra Leone have been falling since the 2014–2016 Ebola epidemic. Data from other LF endemic countries suggest that this is not a true reflection of local epidemiological decline, but rather a function of either health seeking behaviour or the health/referral system. In Sierra Leone, many other diseases present with a similar early clinical picture, including COVID-19 and Marburg Disease (which has recently emerged in neighbouring Guinea). This empirical study explores the implementation of health system processes associated with International Health Regulations (IHR) requirements for early detection and timely and effective responses to the spread of febrile disease, through the case study of LF in Sierra Leone.Methodology/Principal findingsThis study used a qualitative approach to analyse local policy and guidance documents, key informant interviews with policy and practice actors, and focus group discussions and in-depth interviews with health care workers (HCWs) and community health workers (CHWs) in Kenema District to examine the ways in which undifferentiated fever surveillance and response policies and processes were implemented in the post-Ebola period. Multiple challenges were identified, including: issues with the LF case definition, approaches to differential diagnosis, specimen transport and the provision of results, and ownership of laboratory data. These issues lead to delays in diagnosis, and potentially worse outcomes for individual patients, as well as affecting the system’s ability to respond to outbreak-prone disease.Conclusions/SignificanceIdentification of ways to improve the system requires balancing vertical disease surveillance programmes against other population health needs. Therefore, health system challenges to early identification of LF specifically have implications for the effectiveness of the wider Integrated Disease Surveillance and Response (IDSR) system in Sierra Leone more generally. Sentinel surveillance or improved surveillance at maternity facilities would help improve viral haemorrhagic fever (VHF) surveillance, as well as knowledge of LF epidemiology. Strengthening surveillance for vertical disease programmes, if correctly targeted, could have downstream benefits for COVID-19 surveillance and response as well as the wider health system—and therefore patient outcomes more generally.     

Cardiometabolic risk factors for COVID-19 susceptibility and severity: A Mendelian randomization analysis

BackgroundEpidemiological studies report associations of diverse cardiometabolic conditions including obesity with COVID-19 illness, but causality has not been established. We sought to evaluate the associations of 17 cardiometabolic traits with COVID-19 susceptibility and severity using 2-sample Mendelian randomization (MR) analyses.Methods and findingsWe selected genetic variants associated with each exposure, including body mass index (BMI), at p < 5 × 10⁻⁸ from genome-wide association studies (GWASs). We then calculated inverse-variance-weighted averages of variant-specific estimates using summary statistics for susceptibility and severity from the COVID-19 Host Genetics Initiative GWAS meta-analyses of population-based cohorts and hospital registries comprising individuals with self-reported or genetically inferred European ancestry. Susceptibility was defined as testing positive for COVID-19 and severity was defined as hospitalization with COVID-19 versus population controls (anyone not a case in contributing cohorts). We repeated the analysis for BMI with effect estimates from the UK Biobank and performed pairwise multivariable MR to estimate the direct effects and indirect effects of BMI through obesity-related cardiometabolic diseases. Using p < 0.05/34 tests = 0.0015 to declare statistical significance, we found a nonsignificant association of genetically higher BMI with testing positive for COVID-19 (14,134 COVID-19 cases/1,284,876 controls, p = 0.002; UK Biobank: odds ratio 1.06 [95% CI 1.02, 1.10] per kg/m²; p = 0.004]) and a statistically significant association with higher risk of COVID-19 hospitalization (6,406 hospitalized COVID-19 cases/902,088 controls, p = 4.3 × 10⁻⁵; UK Biobank: odds ratio 1.14 [95% CI 1.07, 1.21] per kg/m², p = 2.1 × 10⁻⁵). The implied direct effect of BMI was abolished upon conditioning on the effect on type 2 diabetes, coronary artery disease, stroke, and chronic kidney disease. No other cardiometabolic exposures tested were associated with a higher risk of poorer COVID-19 outcomes. Small study samples and weak genetic instruments could have limited the detection of modest associations, and pleiotropy may have biased effect estimates away from the null.ConclusionsIn this study, we found genetic evidence to support higher BMI as a causal risk factor for COVID-19 susceptibility and severity. These results raise the possibility that obesity could amplify COVID-19 disease burden independently or through its cardiometabolic consequences and suggest that targeting obesity may be a strategy to reduce the risk of severe COVID-19 outcomes.

Aaron Leong and co-workers investigate causal risk factors for COVID-10 illness and severity.     

Ethnic inequalities in COVID-19 vaccine uptake and comparison to seasonal influenza vaccine uptake in Greater Manchester,UK: A cohort study

BackgroundCOVID-19 vaccine uptake is lower amongst most minority ethnic groups compared to the White British group in England, despite higher COVID-19 mortality rates. Here, we add to existing evidence by estimating inequalities for 16 minority ethnic groups, examining ethnic inequalities within population subgroups, and comparing the magnitudes of ethnic inequalities in COVID-19 vaccine uptake to those for routine seasonal influenza vaccine uptake.Methods and findingsWe conducted a retrospective cohort study using the Greater Manchester Care Record, which contains de-identified electronic health record data for the population of Greater Manchester, England. We used Cox proportional hazards models to estimate ethnic inequalities in time to COVID-19 vaccination amongst people eligible for vaccination on health or age (50+ years) criteria between 1 December 2020 and 18 April 2021 (138 days of follow-up). We included vaccination with any approved COVID-19 vaccine, and analysed first-dose vaccination only. We compared inequalities between COVID-19 and influenza vaccine uptake adjusting by age group and clinical risk, and used subgroup analysis to identify populations where inequalities were widest. The majority of individuals (871,231; 79.24%) were White British. The largest minority ethnic groups were Pakistani (50,268; 4.75%), ‘other White background’ (43,195; 3.93%), ‘other ethnic group’ (34,568; 3.14%), and Black African (18,802; 1.71%). In total, 83.64% (919,636/1,099,503) of eligible individuals received a COVID-19 vaccine. Uptake was lower compared to the White British group for 15 of 16 minority ethnic groups, with particularly wide inequalities amongst the groups ‘other Black background’ (hazard ratio [HR] 0.42, 95% CI 0.40 to 0.44), Black African (HR 0.43, 95% CI 0.42 to 0.44), Arab (HR 0.43, 95% CI 0.40 to 0.48), and Black Caribbean (HR 0.43, 95% CI 0.42 to 0.45). In total, 55.71% (419,314/752,715) of eligible individuals took up influenza vaccination. Compared to the White British group, inequalities in influenza vaccine uptake were widest amongst the groups ‘White and Black Caribbean’ (HR 0.63, 95% CI 0.58 to 0.68) and ‘White and Black African’ (HR 0.67, 95% CI 0.63 to 0.72). In contrast, uptake was slightly higher than the White British group amongst the groups ‘other ethnic group’ (HR 1.11, 95% CI 1.09 to 1.12) and Bangladeshi (HR 1.08, 95% CI 1.05 to 1.11). Overall, ethnic inequalities in vaccine uptake were wider for COVID-19 than influenza vaccination for 15 of 16 minority ethnic groups. COVID-19 vaccine uptake inequalities also existed amongst individuals who previously took up influenza vaccination. Ethnic inequalities in COVID-19 vaccine uptake were concentrated amongst older and extremely clinically vulnerable adults, and the most income-deprived. A limitation of this study is the focus on uptake of the first dose of COVID-19 vaccination, rather than full COVID-19 vaccination.ConclusionsEthnic inequalities in COVID-19 vaccine uptake exceeded those for influenza vaccine uptake, existed amongst those recently vaccinated against influenza, and were widest amongst those with greatest COVID-19 risk. This suggests the COVID-19 vaccination programme has created additional and different inequalities beyond pre-existing health inequalities. We suggest that further research and policy action is needed to understand and remove barriers to vaccine uptake, and to build trust and confidence amongst minority ethnic communities.

Ruth Elizabeth Watkinson and colleagues estimate inequalities in Covid-19 vaccine uptake for 16 minority ethnic groups and compare them to those in routine seasonal Influenza vaccine uptake.     

Trio under threat: can we secure the future of rhinos,elephants and tigers in Malaysia?

Three of Malaysia’s endangered large mammal species are experiencing contrasting futures. Populations of the Sumatran rhino (Dicerorhinus sumatrensis) have dwindled to critically low numbers in Peninsular Malaysia (current estimates need to be revised) and the state of Sabah (less than 40 individuals estimated). In the latter region, a bold intervention involving the translocation of isolated rhinos is being developed to concentrate them into a protected area to improve reproduction success rates. For the Asian elephant (Elephas maximus), recently established baselines for Peninsular Malaysia (0.09 elephants/km² estimated from one site) and Sabah (between 0.56 and 2.15 elephants/km² estimated from four sites) seem to indicate globally significant populations based on dung count surveys. Similar surveys are required to monitor elephant population trends at these sites and to determine baselines elsewhere. The population status of the Malayan tiger (Panthera tigris jacksoni) in Peninsular Malaysia, however, remains uncertain as only a couple of scientifically defensible camera-trapping surveys (1.66 and 2.59 tigers/100 km² estimated from two sites) have been conducted to date. As conservation resources are limited, it may be prudent to focus tiger monitoring and protection efforts in priority areas identified by the National Tiger Action Plan for Malaysia. Apart from reviewing the conservation status of rhinos, elephants and tigers and threats facing them, we highlight existing and novel conservation initiatives, policies and frameworks that can help secure the long-term future of these iconic species in Malaysia.     

Universal healthcare coverage and health service delivery before and during the COVID-19 pandemic: A difference-in-difference study of childhood immunization coverage from 195 countries

BackgroundSeveral studies have indicated that universal health coverage (UHC) improves health service utilization and outcomes in countries. These studies, however, have primarily assessed UHC’s peacetime impact, limiting our understanding of UHC’s potential protective effects during public health crises such as the Coronavirus Disease 2019 (COVID-19) pandemic. We empirically explored whether countries’ progress toward UHC is associated with differential COVID-19 impacts on childhood immunization coverage.Methods and findingsUsing a quasi-experimental difference-in-difference (DiD) methodology, we quantified the relationship between UHC and childhood immunization coverage before and during the COVID-19 pandemic. The analysis considered 195 World Health Organization (WHO) member states and their ability to provision 12 out of 14 childhood vaccines between 2010 and 2020 as an outcome. We used the 2019 UHC Service Coverage Index (UHC SCI) to divide countries into a “high UHC index” group (UHC SCI ≥80) and the rest. All analyses included potential confounders including the calendar year, countries’ income group per the World Bank classification, countries’ geographical region as defined by WHO, and countries’ preparedness for an epidemic/pandemic as represented by the Global Health Security Index 2019. For robustness, we replicated the analysis using a lower cutoff value of 50 for the UHC index. A total of 20,230 country-year observations were included in the study. The DiD estimators indicated that countries with a high UHC index (UHC SCI ≥80, n = 35) had a 2.70% smaller reduction in childhood immunization coverage during the pandemic year of 2020 as compared to the countries with UHC index less than 80 (DiD coefficient 2.70; 95% CI: 0.75, 4.65; p-value = 0.007). This relationship, however, became statistically nonsignificant at the lower cutoff value of UHC SCI <50 (n = 60). The study’s primary limitation was scarce data availability, which restricted our ability to account for confounders and to test our hypothesis for other relevant outcomes.ConclusionsWe observed that countries with greater progress toward UHC were associated with significantly smaller declines in childhood immunization coverage during the pandemic. This identified association may potentially provide support for the importance of UHC in building health system resilience. Our findings strongly suggest that policymakers should continue to advocate for achieving UHC in coming years.

In a difference-in-difference study, Sooyoung Kim and colleagues study associations between progress toward universal healthcare coverage and childhood immunizations before and during the COVID-19 pandemic.     

Digital contact tracing and network theory to stop the spread of COVID-19 using big-data on human mobility geolocalization

The spread of COVID-19 caused by the SARS-CoV-2 virus has become a worldwide problem with devastating consequences. Here, we implement a comprehensive contact tracing and network analysis to find an optimized quarantine protocol to dismantle the chain of transmission of coronavirus with minimal disruptions to society. We track billions of anonymized GPS human mobility datapoints to monitor the evolution of the contact network of disease transmission before and after mass quarantines. As a consequence of the lockdowns, people’s mobility decreases by 53%, which results in a drastic disintegration of the transmission network by 90%. However, this disintegration did not halt the spreading of the disease. Our analysis indicates that superspreading k-core structures persist in the transmission network to prolong the pandemic. Once the k-cores are identified, an optimized strategy to break the chain of transmission is to quarantine a minimal number of ‘weak links’ with high betweenness centrality connecting the large k-cores.     

Contact tracing efficiency,transmission heterogeneity,and accelerating COVID-19 epidemics

Simultaneously controlling COVID-19 epidemics and limiting economic and societal impacts presents a difficult challenge, especially with limited public health budgets. Testing, contact tracing, and isolating/quarantining is a key strategy that has been used to reduce transmission of SARS-CoV-2, the virus that causes COVID-19 and other pathogens. However, manual contact tracing is a time-consuming process and as case numbers increase a smaller fraction of cases’ contacts can be traced, leading to additional virus spread. Delays between symptom onset and being tested (and receiving results), and a low fraction of symptomatic cases being tested and traced can also reduce the impact of contact tracing on transmission. We examined the relationship between increasing cases and delays and the pathogen reproductive number R_t, and the implications for infection dynamics using deterministic and stochastic compartmental models of SARS-CoV-2. We found that R_t increased sigmoidally with the number of cases due to decreasing contact tracing efficacy. This relationship results in accelerating epidemics because R_t initially increases, rather than declines, as infections increase. Shifting contact tracers from locations with high and low case burdens relative to capacity to locations with intermediate case burdens maximizes their impact in reducing R_t (but minimizing total infections may be more complicated). Contact tracing efficacy decreased sharply with increasing delays between symptom onset and tracing and with lower fraction of symptomatic infections being tested. Finally, testing and tracing reductions in R_t can sometimes greatly delay epidemics due to the highly heterogeneous transmission dynamics of SARS-CoV-2. These results demonstrate the importance of having an expandable or mobile team of contact tracers that can be used to control surges in cases. They also highlight the synergistic value of high capacity, easy access testing and rapid turn-around of testing results, and outreach efforts to encourage symptomatic cases to be tested immediately after symptom onset.     

Factors associated with the unwillingness of Jordanians,Palestinians and Syrians to be vaccinated against COVID-19

BackgroundThe COVID-19 pandemic is expected to continue to inflect immense burdens of morbidity and mortality, not to mention the sever disruption of societies and economies worldwide. One of the major challenges to managing COVID-19 pandemic is the negative attitudes towards vaccines and the uncertainty or unwillingness to receive vaccinations. We evaluated the predictors and factors behind the negative attitudes towards COVID-19 vaccines in 3 countries in the Middle East.MethodsA cross-sectional, self-administered survey was conducted between the 1^st and the 25^th of December, 2020. Representative sample of 8619 adults residing in Jordan, West Bank, and Syria, completed the survey via the Web or via telephone interview. The survey intended to assess intent to be vaccinated against COVID-19 and to identify predictors of and reasons among participants unwilling/hesitant to get vaccinated.ResultsThe total of the 8619 participants included in this study were the ones who answered the question on the intent to be vaccinated. Overall, 32.2% of participants (n = 2772) intended to be vaccinated, 41.6% (n = 3589) didn’t intend to get vaccinated, and 26.2% (n = 2258) were not sure. The main factors associated with the willingness to take the vaccine (yes responses) included females, 18–35 years old, Syrians and Jordanians, a large family size, and having received a flu vaccine last year. Reasons for vaccine hesitancy included the lack of rigorous evaluation of the vaccine by the FDA and the possible long-term health risks associated with the vaccines (the wait-and-see approach).ConclusionThis survey, conducted in December when the number of cases and deaths per day due to COVID-19 were at or near peak levels of the initial surge in the three regions under investigation. The survey revealed that most of survey’s participants (67.8%) were unwilling/hesitant to get vaccinated against COVID-19 with the lack of trust in the approval process of the vaccine being the main concern; the two main characteristics of those participants were more than 35 years old and participants holding a Bachelor’s degree or higher. Targeted and multi-pronged efforts will be needed to increase acceptance of COVID-19 vaccine in Jordan, West Bank and Syria.     

Parallels,differences and lessons: a comparison of the management of foot-and-mouth disease and COVID-19 using UK 2001/2020 as points of reference

Foot-and-mouth disease (FMD) is an extremely infectious viral infection of cloven-hoofed animals which is highly challenging to control and can give rise to national animal health crises, especially if there is a lack of pre-existing immunity due to the emergence of new strains or following incursions into disease-free regions. The 2001 FMD epidemic in the UK was on a scale that initially overwhelmed the national veterinary services and was eventually controlled by livestock lockdown and slaughter on an unprecedented scale. In 2020, the rapid emergence of COVID-19 has led to a human pandemic unparalleled in living memory. The enormous logistics of multi-agency control efforts for COVID-19 are reminiscent of the 2001 FMD epidemic in the UK, as are the use of movement restrictions, not normally a feature of human disease control. The UK experience is internationally relevant as few countries have experienced national epidemic crises for both diseases. In this review, we reflect on the experiences and lessons learnt from UK and international responses to FMD and COVID-19 with respect to their management, including the challenge of preclinical viral transmission, threat awareness, early detection, different interpretations of scientific information, lockdown, biosecurity behaviour change, shortage of testing capacity and the choices for eradication versus living with infection. A major lesson is that the similarity of issues and critical resources needed to manage large-scale outbreaks demonstrates that there is benefit to a ‘One Health’ approach to preparedness, with potential for greater cooperation in planning and the consideration of shared critical resources.     

World Health Organization Estimates of the Relative Contributions of Food to the Burden of Disease Due to Selected Foodborne Hazards: A Structured Expert Elicitation

Background

The Foodborne Disease Burden Epidemiology Reference Group (FERG) was established in 2007 by the World Health Organization (WHO) to estimate the global burden of foodborne diseases (FBDs). This estimation is complicated because most of the hazards causing FBD are not transmitted solely by food; most have several potential exposure routes consisting of transmission from animals, by humans, and via environmental routes including water. This paper describes an expert elicitation study conducted by the FERG Source Attribution Task Force to estimate the relative contribution of food to the global burden of diseases commonly transmitted through the consumption of food.

Methods and Findings

We applied structured expert judgment using Cooke’s Classical Model to obtain estimates for 14 subregions for the relative contributions of different transmission pathways for eleven diarrheal diseases, seven other infectious diseases and one chemical (lead). Experts were identified through international networks followed by social network sampling. Final selection of experts was based on their experience including international working experience. Enrolled experts were scored on their ability to judge uncertainty accurately and informatively using a series of subject-matter specific ‘seed’ questions whose answers are unknown to the experts at the time they are interviewed. Trained facilitators elicited the 5^th, and 50^th and 95^th percentile responses to seed questions through telephone interviews. Cooke’s Classical Model uses responses to the seed questions to weigh and aggregate expert responses. After this interview, the experts were asked to provide 5^th, 50^th, and 95^th percentile estimates for the ‘target’ questions regarding disease transmission routes. A total of 72 experts were enrolled in the study. Ten panels were global, meaning that the experts should provide estimates for all 14 subregions, whereas the nine panels were subregional, with experts providing estimates for one or more subregions, depending on their experience in the region. The size of the 19 hazard-specific panels ranged from 6 to 15 persons with several experts serving on more than one panel. Pathogens with animal reservoirs (e.g. non-typhoidal Salmonella spp. and Toxoplasma gondii) were in general assessed by the experts to have a higher proportion of illnesses attributable to food than pathogens with mainly a human reservoir, where human-to-human transmission (e.g. Shigella spp. and Norovirus) or waterborne transmission (e.g. Salmonella Typhi and Vibrio cholerae) were judged to dominate. For many pathogens, the foodborne route was assessed relatively more important in developed subregions than in developing subregions. The main exposure routes for lead varied across subregions, with the foodborne route being assessed most important only in two subregions of the European region.

Conclusions

For the first time, we present worldwide estimates of the proportion of specific diseases attributable to food and other major transmission routes. These findings are essential for global burden of FBD estimates. While gaps exist, we believe the estimates presented here are the best current source of guidance to support decision makers when allocating resources for control and intervention, and for future research initiatives.     

Modeling the epidemiological impact of the UNAIDS 2025 targets to end AIDS as a public health threat by 2030

BackgroundUNAIDS has established new program targets for 2025 to achieve the goal of eliminating AIDS as a public health threat by 2030. This study reports on efforts to use mathematical models to estimate the impact of achieving those targets.Methods and findingsWe simulated the impact of achieving the targets at country level using the Goals model, a mathematical simulation model of HIV epidemic dynamics that includes the impact of prevention and treatment interventions. For 77 high-burden countries, we fit the model to surveillance and survey data for 1970 to 2020 and then projected the impact of achieving the targets for the period 2019 to 2030. Results from these 77 countries were extrapolated to produce estimates for 96 others. Goals model results were checked by comparing against projections done with the Optima HIV model and the AIDS Epidemic Model (AEM) for selected countries. We included estimates of the impact of societal enablers (access to justice and law reform, stigma and discrimination elimination, and gender equality) and the impact of Coronavirus Disease 2019 (COVID-19). Results show that achieving the 2025 targets would reduce new annual infections by 83% (71% to 86% across regions) and AIDS-related deaths by 78% (67% to 81% across regions) by 2025 compared to 2010. Lack of progress on societal enablers could endanger these achievements and result in as many as 2.6 million (44%) cumulative additional new HIV infections and 440,000 (54%) more AIDS-related deaths between 2020 and 2030 compared to full achievement of all targets. COVID-19–related disruptions could increase new HIV infections and AIDS-related deaths by 10% in the next 2 years, but targets could still be achieved by 2025. Study limitations include the reliance on self-reports for most data on behaviors, the use of intervention effect sizes from published studies that may overstate intervention impacts outside of controlled study settings, and the use of proxy countries to estimate the impact in countries with fewer than 4,000 annual HIV infections.ConclusionsThe new targets for 2025 build on the progress made since 2010 and represent ambitious short-term goals. Achieving these targets would bring us close to the goals of reducing new HIV infections and AIDS-related deaths by 90% between 2010 and 2030. By 2025, global new infections and AIDS deaths would drop to 4.4 and 3.9 per 100,000 population, and the number of people living with HIV (PLHIV) would be declining. There would be 32 million people on treatment, and they would need continuing support for their lifetime. Incidence for the total global population would be below 0.15% everywhere. The number of PLHIV would start declining by 2023.

John Stover and co-workers assess the potential health impacts of UNAIDS’ HIV/AIDS targets.     

Investigating associations between COVID-19 mortality and population-level health and socioeconomic indicators in the United States: A modeling study

BackgroundWith the availability of multiple Coronavirus Disease 2019 (COVID-19) vaccines and the predicted shortages in supply for the near future, it is necessary to allocate vaccines in a manner that minimizes severe outcomes, particularly deaths. To date, vaccination strategies in the United States have focused on individual characteristics such as age and occupation. Here, we assess the utility of population-level health and socioeconomic indicators as additional criteria for geographical allocation of vaccines.Methods and findingsCounty-level estimates of 14 indicators associated with COVID-19 mortality were extracted from public data sources. Effect estimates of the individual indicators were calculated with univariate models. Presence of spatial autocorrelation was established using Moran’s I statistic. Spatial simultaneous autoregressive (SAR) models that account for spatial autocorrelation in response and predictors were used to assess (i) the proportion of variance in county-level COVID-19 mortality that can explained by identified health/socioeconomic indicators (R²); and (ii) effect estimates of each predictor.Adjusting for case rates, the selected indicators individually explain 24%–29% of the variability in mortality. Prevalence of chronic kidney disease and proportion of population residing in nursing homes have the highest R². Mortality is estimated to increase by 43 per thousand residents (95% CI: 37–49; p < 0.001) with a 1% increase in the prevalence of chronic kidney disease and by 39 deaths per thousand (95% CI: 34–44; p < 0.001) with 1% increase in population living in nursing homes. SAR models using multiple health/socioeconomic indicators explain 43% of the variability in COVID-19 mortality in US counties, adjusting for case rates. R² was found to be not sensitive to the choice of SAR model form. Study limitations include the use of mortality rates that are not age standardized, a spatial adjacency matrix that does not capture human flows among counties, and insufficient accounting for interaction among predictors.ConclusionsSignificant spatial autocorrelation exists in COVID-19 mortality in the US, and population health/socioeconomic indicators account for a considerable variability in county-level mortality. In the context of vaccine rollout in the US and globally, national and subnational estimates of burden of disease could inform optimal geographical allocation of vaccines.

Sasikiran Kandula and Jeffrey Shaman study population health and COVID-19 mortality in the United States.     

The elimination of human African trypanosomiasis: Achievements in relation to WHO road map targets for 2020

BackgroundIn the 20th century, epidemics of human African trypanosomiasis (HAT) ravaged communities in a number of African countries. The latest surge in disease transmission was recorded in the late 1990s, with more than 35,000 cases reported annually in 1997 and 1998. In 2013, after more than a decade of sustained control efforts and steady progress, the World Health Assembly resolved to target the elimination of HAT as a public health problem by 2020. We report here on recent progress towards this goal.Methodology/principal findingsWith 992 and 663 cases reported in 2019 and 2020 respectively, the first global target was amply achieved (i.e. fewer than 2,000 HAT cases/year). Areas at moderate or higher risk of HAT, where more than 1 case/10,000 people/year are reported, shrunk to 120,000 km² for the five-year period 2016–2020. This reduction of 83% from the 2000–2004 baseline (i.e. 709,000 km²) is slightly below the target (i.e. 90% reduction). As a result, the second global target for HAT elimination as a public health problem cannot be considered fully achieved yet. The number of health facilities able to diagnose and treat HAT expanded (+9.6% compared to a 2019 survey), thus reinforcing the capacity for passive detection and improving epidemiological knowledge of the disease. Active surveillance for gambiense HAT was sustained. In particular, 2.8 million people were actively screened in 2019 and 1.6 million in 2020, the decrease in 2020 being mainly caused by COVID-19-related restrictions. Togo and Côte d’Ivoire were the first countries to be validated for achieving elimination of HAT as a public health problem at the national level; applications from three additional countries are under review by the World Health Organization (WHO).Conclusions/significanceThe steady progress towards the elimination of HAT is a testament to the power of multi-stakeholder commitment and coordination. At the end of 2020, the World Health Assembly endorsed a new road map for 2021–2030 that set new bold targets for neglected tropical diseases. While rhodesiense HAT remains among the diseases targeted for elimination as a public health problem, gambiense HAT is targeted for elimination of transmission. The goal for gambiense HAT is expected to be particularly arduous, as it might be hindered by cryptic reservoirs and a number of other challenges (e.g. further integration of HAT surveillance and control into national health systems, availability of skilled health care workers, development of more effective and adapted tools, and funding for and coordination of elimination efforts).