Autoantibodies against type I interferons in COVID-19 infection: A systematic review and meta-analysis.

OBJECTIVES: In this study, we aimed to study the rate of autoantibodies against type I interferons (IFNs) in patients with COVID-19 and analyze its dependence on severity of infection and some other variables. METHODS: A systemic review with the search terms: "COVID-19" or "SARS-CoV-2" and "autoantibodies" or "autoantibody" and "IFN" or "interferon" for the period 20 December 2019 to 15 August 2022 was carried out using PubMed, Embase, Cochrane, and Web of Science. R 4.2.1 software was used for meta-analysis of the published results. Pooled risk ratios and 95% confidence intervals (CIs) were calculated. RESULTS: We identified eight studies involving 7729 patients, of whom 5097 (66%) had severe COVID-19 and 2632 (34%) had mild or moderate symptoms. The positive rate of anti-type-I-IFN-autoantibodies in the total dataset was 5% (95% CI, 3-8%), but reached 10% (95% CI, 7-14%) in those with severe infection. The most common subtypes were anti-IFN-α (89%) and anti-IFN-ω (77%). The overall prevalence in male patients was 5% (95% CI, 4-6%), and in female patients 2% (95% CI, 1-3%). CONCLUSION: Severe COVID-19 is associated with high rates of autoantibodies against type-I-IFN and more so in male than female patients.

Challenges and response to pandemics as seen in a One Health perspective

The global pandemic caused by the coronavirus disease 2019 not only exposed the fragility of global preparedness and response to public health emergence, but also illustrated the fragmentation and gaps of research and development ecosystem. This emphasizes the need for planned actions against the potentiality of new pandemics and requires research to better understand how viruses bridge the animal/human divide making human-to-human transmission of new diseases possible. Major challenges to response to new epidemics under the current health framework reside in the so called 4-CC approach that focuses on Concept, Communication, Coherence, and Continuity. There is a need to also add a One Health perspective with emphasis on governance, surveillance, capacity building and multi-disciplinary research to achieve a holistic and better integrated system. Using a regulatory framework to equip professionals might facilitate the function of a multi-sector approach that recognizes the value of their mandates and a One Health approach in their work. Collaborative, multisectoral actions under the global regulations and guidance would make evidence-based One Health approaches sustainable and accessible to everyone.

The COVID-19 Mortality Rate Is Associated with Illiteracy, Age, and Air Pollution in Urban Neighborhoods: A Spatiotemporal Cross-Sectional Analysis.

There are different area-based factors affecting the COVID-19 mortality rate in urban areas. This research aims to examine COVID-19 mortality rates and their geographical association with various socioeconomic and ecological determinants in 350 of Tehran's neighborhoods as a big city. All deaths related to COVID-19 are included from December 2019 to July 2021. Spatial techniques, such as Kulldorff's SatScan, geographically weighted regression (GWR), and multi-scale GWR (MGWR), were used to investigate the spatially varying correlations between COVID-19 mortality rates and predictors, including air pollutant factors, socioeconomic status, built environment factors, and public transportation infrastructure. The city's downtown and northern areas were found to be significantly clustered in terms of spatial and temporal high-risk areas for COVID-19 mortality. The MGWR regression model outperformed the OLS and GWR regression models with an adjusted R2 of 0.67. Furthermore, the mortality rate was found to be associated with air quality (e.g., NO2, PM10, and O3); as air pollution increased, so did mortality. Additionally, the aging and illiteracy rates of urban neighborhoods were positively associated with COVID-19 mortality rates. Our approach in this study could be implemented to study potential associations of area-based factors with other emerging infectious diseases worldwide.

COVID-19: Past, present and future.

Not available.

Consideration of COVID-19 beyond the human-centred approach of prevention and control: the ONE-HEALTH perspective.

Most of the new emerging and re-emerging zoonotic virus outbreaks in recent years stem from close interaction with dead or alive infected animals. Since late 2019, the coronavirus disease 2019 (COVID-19) has spread into 221 countries and territories resulting in close to 300 million known infections and 5.4 million deaths in addition to a huge impact on both public health and the world economy. This paper reviews the COVID-19 prevalence in animals, raise concerns about animal welfare and discusses the role of environment in the transmission of COVID-19. Attention is drawn to the One Health concept as it emphasizes the environment in connection with the risk of transmission and establishment of diseases shared between animals and humans. Considering the importance of One Health for an effective response to the dissemination of infections of pandemic character, some unsettled issues with respect to COVID-19 are highlighted.

Measuring COVID-19 vaccination coverage: an enhanced age-adjusted two-step floating catchment area model.

BACKGROUND: There are only limited studies on access to COVID-19 vaccines and identifying the most appropriate health centres for performing vaccination in metropolitan areas. This study aimed to measure potential spatial access to COVID-19 vaccination centres in Mashhad, the second-most populous city in Iran. METHODS: The 2021 age structure of the urban census tracts was integrated into the enhanced two-step floating catchment area model to improve accuracy. The model was developed based on three different access scenarios: only public hospitals, only public healthcare centres and both (either hospitals or healthcare centres) as potential vaccination facilities. The weighted decision-matrix and analytic hierarchy process, based on four criteria (i.e. service area, accessibility index, capacity of vaccination centres and distance to main roads), were used to choose potential vaccination centres looking for the highest suitability for residents. Global Moran's index (GMI) was used to measure the spatial autocorrelation of the accessibility index in different scenarios and the proposed model. RESULTS: There were 26 public hospitals and 271 public healthcare centres in the study area. Although the exclusive use of public healthcare centres for vaccination can provide the highest accessibility in the eastern and north-eastern parts of the study area, our findings indicate that including both public hospitals and public healthcare centres provide high accessibility to vaccination in central urban part. Therefore, a combination of public hospitals and public healthcare centres is recommended for efficient vaccination coverage. The value of GMI for the proposed model (accessibility to selected vaccination centres) was calculated as 0.53 (Z = 162.42, P < 0.01). Both GMI and Z-score values decreased in the proposed model, suggesting an enhancement in accessibility to COVID-19 vaccination services. CONCLUSIONS: The periphery and poor areas of the city had the least access to COVID-19 vaccination centres. Measuring spatial access to COVID-19 vaccination centres can provide valuable insights for urban public health decision-makers. Our model, coupled with geographical information systems, provides more efficient vaccination coverage by identifying the most suitable healthcare centres, which is of special importance when only few centres are available.

A Spatial Analysis of COVID-19 in African Countries: Evaluating the Effects of Socio-Economic Vulnerabilities and Neighbouring.

The ongoing highly contagious coronavirus disease 2019 (COVID-19) pandemic, which started in Wuhan, China, in December 2019, has now become a global public health problem. Using publicly available data from the COVID-19 data repository of Our World in Data, we aimed to investigate the influences of spatial socio-economic vulnerabilities and neighbourliness on the COVID-19 burden in African countries. We analyzed the first wave (January-September 2020) and second wave (October 2020 to May 2021) of the COVID-19 pandemic using spatial statistics regression models. As of 31 May 2021, there was a total of 4,748,948 confirmed COVID-19 cases, with an average, median, and range per country of 101,041, 26,963, and 2191 to 1,665,617, respectively. We found that COVID-19 prevalence in an Africa country was highly dependent on those of neighbouring Africa countries as well as its economic wealth, transparency, and proportion of the population aged 65 or older (p-value < 0.05). Our finding regarding the high COVID-19 burden in countries with better transparency and higher economic wealth is surprising and counterintuitive. We believe this is a reflection on the differences in COVID-19 testing capacity, which is mostly higher in more developed countries, or data modification by less transparent governments. Country-wide integrated COVID suppression strategies such as limiting human mobility from more urbanized to less urbanized countries, as well as an understanding of a county's social-economic characteristics, could prepare a country to promptly and effectively respond to future outbreaks of highly contagious viral infections such as COVID-19.

A spatial-epidemiological dataset of subjects infected by SARS-CoV-2 during the first wave of the pandemic in Mashhad, second-most populous city in Iran.

OBJECTIVE: In March 2020, Iran tackled the first national wave of COVID-19 that was particularly felt in Mashhad, Iran's second-most populous city. Accordingly, we performed a spatio-temporal study in this city to investigate the epidemiological aspects of the disease in an urban area and now wish to release a comprehensive dataset resulting from this study. DATA DESCRIPTION: These data include two data files and a help file. Data file 1: "COVID-19_Patients_Data" contains the patient sex and age + time from symptoms onset to hospital admission; hospitalization time; co-morbidities; manifest symptoms; exposure up to 14 days before admission; disease severity; diagnosis (with or without RT-PCR assay); and outcome (recovery vs. death). The data covers 4000 COVID-19 patients diagnosed between 14 Feb 2020 and 11 May 2020 in Khorasan-Razavi Province. Data file 2: "COVID-19_Spatiotemporal_Data" is a digital map of census tract divisions of Mashhad, the capital of the province, and their population by gender along with the number of COVID-19 cases and deaths including the calculated rates per 100,000 persons. This dataset can be a valuable resource for epidemiologists and health policymakers to identify potential risk factors, control and prevent pandemics, and optimally allocate health resources.

Genetic Aspects and Immune Responses in Covid-19: Important Organ Involvement.

In the last two decades, the world has experienced outbreaks of three major coronaviruses with high morbidity and mortality rates. The most recent of these started in the form of an unusual viral pneumonia in Wuhan, China, and now the world is facing a serious pandemic. This new disease has been called COVID-19 and is caused by the SARS-CoV-2 virus. Understanding the specific genetic and phenotypic structure of SARS-CoV-2 in COVID-19 pathogenesis is vital in finding appropriate drugs and vaccines. With this in mind, this review sheds light on the virology, genetics, immune-responses, and mechanism of action of this virus.

Epidemiological characteristics and initial spatiotemporal visualisation of COVID-19 in a major city in the Middle East.

BACKGROUND: The Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) emerged initially in China in December 2019 causing the COVID-19 disease, which quickly spread worldwide. Iran was one of the first countries outside China to be affected in a major way and is now under the spell of a fourth wave. This study aims to investigate the epidemiological characteristics of COVID-19 cases in north-eastern Iran through mapping the spatiotemporal trend of the disease. METHODS: The study comprises data of 4000 patients diagnosed by laboratory assays or clinical investigation from the beginning of the disease on Feb 14, 2020, until May 11, 2020. Epidemiological features and spatiotemporal trends of the disease in the study area were explored by classical statistical approaches and Geographic Information Systems. RESULTS: Most common symptoms were dyspnoea (69.4%), cough (59.4%), fever (54.4%) and weakness (19.5%). Approximately 82% of those who did not survive suffered from dyspnoea. The highest Case Fatality Rate (CFR) was related to those with cardiovascular disease (27.9%) and/or diabetes (18.1%). Old age (≥60 years) was associated with an almost five-fold increased CFR. Odds Ratio (OR) showed malignancy (3.8), nervous diseases (2.2), and respiratory diseases (2.2) to be significantly associated with increased CFR with developments, such as hospitalization at the ICU (2.9) and LOS (1.1) also having high correlations. Furthermore, spatial analyses revealed a geographical pattern in terms of both incidence and mortality rates, with COVID-19 first being observed in suburban areas from where the disease swiftly spread into downtown reaching a peak between 25 February to 06 March (4 incidences per km2). Mortality peaked 3 weeks later after which the infection gradually decreased. Out of patients investigated by the spatiotemporal approach (n = 727), 205 (28.2%) did not survive and 66.8% of them were men. CONCLUSIONS: Older adults and people with severe co-morbidities were at higher risk for developing serious complications due to COVID-19. Applying spatiotemporal methods to identify the transmission trends and high-risk areas can rapidly be documented, thereby assisting policymakers in designing and implementing tailored interventions to control and prevent not only COVID-19 but also other rapidly spreading epidemics/pandemics.

Demographic and clinical characteristics of severe Covid-19 infections: a cross-sectional study from Mashhad University of Medical Sciences, Iran.

BACKGROUND: Coronavirus Disease 2019 (Covid-19) is expanding worldwide. The characteristics of this infection in patients varies from country to country. To move forward, clinical data on infected patients are needed. Here, we report a comparison between fatalities and recovery of patients with severe Covid-19, based on demographic and clinical characteristics. METHODS: Between 5 March and 12 May 2020 in Mashhad, Iran, 1278 of 4000 suspected Covid-19 patients were confirmed positive by real-time reverse-transcriptase-polymerase-chain-reaction assay of upper respiratory specimens. We compared the demographic, exposure history and clinical symptoms of 925 survivors and 353 fatal cases with confirmed disease. RESULTS: Mean (SD) age for all confirmed patients was 56.9 (18.7) years, 67.1 (15.9) years in fatal cases and 53.0 (18.3) years in survivors. Multivariate logistic regression analysis showed that the outcome of patients was associated with age (odds ratio = 1.049, P = 0.0001, 95% CI = 1.040-1.057). Despite a high burden of Covid-19 infections in the 30-39 and 40-49 year age groups, most of these (89.6 and 87.2%, respectively) recovered. The median (IQR) duration of hospitalization was 9.0 (6.0-14.0) days. The most prevalent co-morbidities were cardiovascular disorders (21%) and diabetes (16.3%). Dyspnoea (72.7%), cough (68.1%) and fever (63.8%) were the most frequent clinical symptoms. Healthcare workers, of whom two (3%) died, comprised 5.2% of infected cases. Combination antiviral and antibiotic therapy was used in 43.0% of cases. CONCLUSIONS: The characteristics of severe Covid-19 varied substantially between fatal cases and survivors, with diabetes and cardiovascular disorders the most prevalent co-morbidities. In contrast to other studies, there were a higher number of fatalities in younger patients in our setting.

Transport geography: Implications for public health.

The obstruction of traffic between France and UK due to efforts to rein in coronavirus 2019 (COVID-19), together with the recent, week-long blockade of the Suez Canal, underline how interconnected and thus vulnerable the world has become. What this has to do with public health may not be immediately evident. However, as illustrated by two papers published in this issue of Geospatial Health dealing with the ongoing waves of COVID-19 spread (Mahmud et al., 2021; Tiwari and Aljoufie, 2021), transport geography - with its focus on geographical dimensions of travel, transport and mobility - does indeed have a direct impact on health and epidemiology...

Meteorological conditions are heterogeneous factors for COVID-19 risk in China.

Whether meteorological factors influence COVID-19 transmission is an issue of major public health concern, but available evidence remains unclear and limited for several reasons, including the use of report date which can lag date of symptom onset by a considerable period. We aimed to generate reliable and robust evidence of this relationship based on date of onset of symptoms. We evaluated important meteorological factors associated with daily COVID-19 counts and effective reproduction number (Rt) in China using a two-stage approach with overdispersed generalized additive models and random-effects meta-analysis. Spatial heterogeneity and stratified analyses by sex and age groups were quantified and potential effect modification was analyzed. Nationwide, there was no evidence that temperature and relative humidity affected COVID-19 incidence and Rt. However, there were heterogeneous impacts on COVID-19 risk across different regions. Importantly, there was a negative association between relative humidity and COVID-19 incidence in Central China: a 1% increase in relative humidity was associated with a 3.92% (95% CI, 1.98%-5.82%) decrease in daily counts. Older population appeared to be more sensitive to meteorological conditions, but there was no obvious difference between sexes. Linear relationships were found between meteorological variables and COVID-19 incidence. Sensitivity analysis confirmed the robustness of the association and the results based on report date were biased. Meteorological factors play heterogenous roles on COVID-19 transmission, increasing the possibility of seasonality and suggesting the epidemic is far from over. Considering potential climatic associations, we should maintain, not ease, current control measures and surveillance.

Covid-19 Presented Only with Gastrointestinal Symptoms: A Case Report of a 14-Year-Old Patient

Coronavirus disease 2019 (Covid-19) is expanding worldwide. Although it seems to be a purely respiratory disease, occasional reports of lesions in other organs have been published. We report here an asymptomatic child with Covid-19 and with the main symptom of abdominal pain distension and without any respiratory symptoms. A 14-year-old male patient with main complaints of fever, malaise, anorexia, and severe abdominal pain was admitted to a hospital in Mashhad, Iran. Laparotomy revealed distension of the small intestine and an adhesive ileocaecal band that had produced ileum herniation without free fluid in the abdomen. Chest radiography and high-resolution computed tomography of the lungs showed bilateral and diffuse, peripheral dense areas of ground-glass appearance. A nasopharyngeal swab for diagnosis of Covid-19, was ordered due to lymphopenia together with these diffuse lung infiltrations, which showed a positive result. This led to drug treatment with lopinavir/ ritonavir, hydroxychloroquine, ribavirin/oseltamivir, and meropenem. The patient was febrile and developed tachycardia on the third day, accompanied by a respiratory rate of 44/min. At this point, tracheal intubation was done, but the patient died after 3 hours due to cardiac arrest. The case report brings forth the hypothesis that the gastrointestinal manifestation may be an atypical symptom of Covid-19 infection and highlights the importance of the diagnosis based on combined laboratory-based data and scanning imagery.

First year with COVID-19: Assessment and prospects.

The vision of health for all by Dr. Halfdan Mahler, Director General of the World Health Organization (WHO) 1973 to 1988, guided public health approaches towards improving life for all those mired in poverty and disease. Research on the Neglected Tropical Diseases (NTDs) of the world's poor was advancing strongly when the coronavirus disease 2019 (COVID-19) struck. Although work on the NTDs did not grind to a halt, the situation is reminiscent of the author Stefan Zweig's passionate account of culture destruction in his book The World of Yesterday from 1941, which gives an insight as to how the war ended traditional life. His thoughts parallel the present situation; however, this time societies are not torn apart by war but instead isolated by a pandemic. It comes upon today's scientists to move fast to make COVID-19 less devastating than the Spanish flu of 1918-1920 that killed more than 3% of the world population...

Covid-19: End of the beginning?

The limited case cluster of atypical pneumonia detected in central China in December 2019, now known as Coronavirus Disease 2019 (Covid-19), converted into a million confirmed cases worldwide in only 10 weeks. Declared a pandemic by the World Health Organization (WHO) on 11 March 2020 (WHO, 2020) and passing the 3 million mark on 27 April, the world is under formidable strain with respect to public health, economy and personal life. Time and again we are alerted about unforeseen, new effects of this disease, which brings to mind the terms "known unknowns" and "unknown unknowns" used by former U.S. Secretary of Defense Donald Rumsfield when referring to the lack of evidence of weapons of mass destruction in Iraq ahead of the second Gulf war, a fitting vocabulary as we again are faced with mass destruction, though this time of a different kind.

Covid-19: Pandemonium in our time.

While pandemonium has come to mean wild and noisy disorder, the reference here is to John Milton's epic poem Paradise Lost and the upheaval following Lucifer's banishment from Heaven and his construction of Pandæmonium as his hub. Today's avalanche of conflicting news on how to deal with the coronavirus disease 2019 (Covid-19) brings to mind the Trinity nuclear bomb test with Enrico Fermi estimating its strength by releasing small pieces of paper into the air and measuring their displacement by the shock wave. Fermi's result, in fact not far from the true value, emphasised his ability to make good approximations with few or no actual data. The current wave of Covid-19 presents just this kind of situation as it engulfs the world from ground zero in Wuhan, China. Much information is indeed missing, but datasets that might lead to useful ideas on how to handle this pandemic are steadily accumulating.