Wave Of Outbreak Research Articles

Clinical Characteristics and Outcomes of Hospitalized COVID-19 Patients with Different Variants of SARS-CoV-2 in a Tertiary Care Hospital, Thailand

The different strains of SARS-CoV-2 were detected and labeled in 2021. Each strain differs in both clinical symptoms and severity. Previous studies found different clinical symptoms and treatment outcomes between outbreak waves; however, data in Southeast Asia were limited. This study collected data of hospitalized COVID-19 patients from a Tertiary hospital in Thailand between January 2020 and December 2023 and analyzed patients’ data in each outbreak wave using Pearson’s chi-square. A total of 1084 inpatients were included for analysis. The median age was 64 (IQR, 0.4–100) years. The patients were hospitalized in predominantly Alpha (22.78%), Delta (21.68%), and Omicron (5.07%) periods of the virus outbreak. The largest age group was elderly (over 65 years old) in all three variant of concern (VOC) periods; 82.65% of the patients had comorbidities, including 58.5% hypertension, 46.5% dyslipidemia, and 42.0% diabetes mellitus (DM). The study found pneumonia at 67.53%, septic shock at 4.61%, acute respiratory distress syndrome (ARDS) at 2.86%, and congestive heart failure at 0.83% in all age groups with no significant difference between outbreak periods. The overall mortality rate was 16.14%. A total of 75% of deaths occurred in patients over 65 years old. The mortality rates in each VOC period were 20.0% Delta, 19.83% Alpha, and 13.23% Omicron. In the elderly group, the mortality rates were Delta 15.32%, Alpha 11.75%, and Omicron 10.88%. The Omicron VOC was less severe than other variants, particularly in the elderly (65 years). There were no significant differences in the younger (<65 years) age group. The elderly still had more severe symptoms and the highest mortality rates in every wave of outbreak.

Predicting susceptibility to COVID-19 infection in patients on maintenance hemodialysis by cross-coupling soluble ACE2 concentration with lymphocyte count: an algorithmic approach.

Patients on maintenance hemodialysis (MHD) were more vulnerable to and had a higher mortality during the COVID-19 pandemic. As angiotensin converting enzyme 2 (ACE2) and transmembrane protease serine S1 member 2 (TMPRSS2) played crucial roles in viral entry into the human host cells, we therefore investigated in the MHD patients whether their plasma levels were associated with susceptibility to the COVID-19. Blood samples were collected from the patients in our then COVID-19 free center immediately upon lifting of the stringent quarantine measures in early December of 2022 and infection situation was observed within the following 2 weeks. Plasma levels of the soluble ACE2 (sACE2), ACE (sACE) and TMPRSS2 (sTMPRSS2) were measured with ELISA method. Data were stepwisely tested for independent effect, relevant role and synergistic action on the susceptibility by multiple logistic regression, receiver operating characteristic curve and multiple dimensionality reduction (MDR) method, respectively. Among the 174 eligible patients, 95 (54.6%) turned COVID-19 positive with a male to female ratio of 1.57 during the observation period. Comparing with the uninfected, the infected had significantly higher sACE2 and lower sTMPRSS2 levels upon comparable sACE concentration. Besides the sACE2, factors associated with susceptibility were vintage and individual session time of the hemodialysis, smoking and comorbidity of hepatitis, whereas lymphocyte counts showed a tendency (p = 0.052). Patients simultaneously manifesting higher sACE2 level and lower lymphocyte counts had an increased infection risk as confirmed by the MDR method. By sorting out the susceptible ones expeditiously, this algorithmic approach may help the otherwise vulnerable MHD patients weather over future wave of COVID-19 variants or outbreak of other viral diseases.

Associations between clinical data, vaccination status, antibody responses, and post-COVID-19 symptoms in Thais infected with SARS-CoV-2 Delta and Omicron variants: a 1-year follow-up study

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), led to a global pandemic from 2020. In Thailand, five waves of outbreaks were recorded, with the fourth and fifth waves driven by the Delta and Omicron variants, resulting in over 20,000 new confirmed cases daily at their peaks.MethodsThis cross-sectional study investigated the associations between clinical symptoms, vaccination status, antibody responses, and post-COVID-19 sequelae in COVID-19 patients. Plasma samples and clinical data were collected from participants admitted to hospitals in Thailand between July 2021 and August 2022, with follow-ups conducted for one year. The study included 110 participants infected with either the Delta (n = 46) or Omicron (n = 64) variants. Virus genotypes were confirmed by RT-PCR of nasal swab RNA and partial nucleotide sequencing of the S gene. IgG and IgA antibody levels against the receptor-binding domain (RBD) of SARS-CoV-2 Delta and Omicron variants were measured in plasma samples using ELISA.ResultsPneumonia was found to be associated with Delta variant infections, while sore throat, congestion or runny nose, and headache were linked to Omicron infections. Vaccination with fewer than two doses and diabetes mellitus were significantly associated with higher disease severity. Specific IgG and IgA antibodies against the RBD of the Delta variant generally rose by day 14 and were maintained for up to two months, whereas the pattern of antibody response to the Omicron variant was less clear. Antibody risings were found to be positively associated with pneumonia, certain underlying conditions (obesity, hypertension, dyslipidemia, and diabetes mellitus), and age ≥ 60 years. Delta variant infections were associated with forgetfulness, hair loss, and headache during the 1-year post-infection period. Females were more likely to experience hair loss, forgetfulness, and joint pain, while older age was associated with joint pain.ConclusionsThis study enhances our understanding of SARS-CoV-2 infections in Thais, particularly concerning the Delta and Omicron variants. The findings can inform public health planning and response strategies for future outbreaks of SARS-CoV-2 or other emerging viral diseases.

Viral genetics and transmission dynamics in the second wave of mpox outbreak in Portugal and forecasting public health scenarios

ABSTRACT In 2023, a second wave of the global mpox epidemic, which is mainly affecting men who have sex with men (MSM), was observed in some countries. Herein, we benefited from a large viral sequence sampling (76/121; 63%) and vast epidemiological data to characterise the re-emergence and circulation of the Monkeypox virus (MPXV) in Portugal during 2023. We also modelled transmission and forecasted public health scenarios through a compartmental susceptible-exposed-infectious-recovered (SEIR) model. Our results suggest that the 2023 mpox wave in Portugal resulted from limited introduction(s) of MPXV belonging to C.1.1 sublineage, hypothetically from Asia, followed by sustained viral transmission and potential exportation to other countries. We estimated that the contribution of the MSM high sexual activity group to mpox transmission was 120 (95% CrI: 30–3553) times higher than that of the low sexual activity group. However, among the high sexual activity group, vaccinated individuals likely contributed approximately eight times less [0.123 (95% CrI: 0.068–0.208)] than the unvaccinated ones. Vaccination was also linked to potential reduced disease severity, with a Mpox Severity Score of 6.0 in the vaccinated group compared to 7.0 in unvaccinated individuals. Scenario analysis indicated that transmission is highly sensitive to sexual behaviour, projecting that a slight increase in the MSM sub-population with high sexual activity can trigger new mpox waves. This study strongly supports that continued vaccination, targeted awareness among risk groups and routine genomic epidemiology is needed to anticipate and respond to novel MPXV threats (e.g. global dissemination of clade I viruses).

A six-compartment model for COVID-19 with transmission dynamics and public health strategies.

The global crisis of the COVID-19 pandemic has highlighted the need for mathematical models to inform public health strategies. The present study introduces a novel six-compartment epidemiological model that uniquely incorporates a higher isolation rate for unreported symptomatic cases of COVID-19 compared to reported cases, aiming to enhance prediction accuracy and address the challenge of initial underreporting. Additionally, we employ optimal control theory to assess the cost-effectiveness of interventions and adapt these strategies to specific epidemiological scenarios, such as varying transmission rates and the presence of asymptomatic carriers. By applying this model to COVID-19 data from India (30 January 2020 to 24 November 2020), chosen to capture the initial outbreak and subsequent waves, we calculate a basic reproduction number of 2.147, indicating the high transmissibility of the virus during this period in India. A sensitivity analysis reveals the critical impact of detection rates and isolation measures on disease progression, showing the robustness of our model in estimating the basic reproduction number. Through optimal control simulations, we demonstrate that increasing isolation rates for unreported cases and enhancing detection reduces the spread of COVID-19. Furthermore, our cost-effectiveness analysis establishes that a combined strategy of isolation and treatment is both more effective and economically viable. This research offers novel insights into the efficacy of non-pharmaceutical interventions, providing a tool for strategizing public health interventions and advancing our understanding of infectious disease dynamics.

Neu5Gc binding loss of subtype H7 influenza A virus facilitates adaptation to gallinaceous poultry following transmission from waterbirds.

Between 2013 and 2018, the novel A/Anhui/1/2013 (AH/13)-lineage H7N9 virus caused at least five waves of outbreaks in humans, totaling 1,567 confirmed human cases in China. Surveillance data indicated a disproportionate distribution of poultry infected with this AH/13-lineage virus, and laboratory experiments demonstrated that this virus can efficiently spread among chickens but not among Pekin ducks. The underlying mechanism of this selective transmission remains unclear. In this study, we demonstrated the absence of Neu5Gc expression in chickens across all respiratory and gastrointestinal tissues. However, Neu5Gc expression varied among different duck species and even within the tissues of the same species. The AH/13-lineage viruses exclusively bind to acetylneuraminic acid (Neu5Ac), in contrast to wild waterbird H7 viruses that bind both Neu5Ac and N-glycolylneuraminic acid (Neu5Gc). The level of Neu5Gc expression influences H7 virus replication and facilitates adaptive mutations in these viruses. In summary, our findings highlight the critical role of Neu5Gc in affecting the host range and interspecies transmission dynamics of H7 viruses among avian species.IMPORTANCEMigratory waterfowl, gulls, and shorebirds are natural reservoirs for influenza A viruses (IAVs) that can occasionally spill over to domestic poultry, and ultimately humans. This study showed wild-type H7 IAVs from waterbirds initially bind to glycan receptors terminated with N-acetylneuraminic acid (Neu5Ac) or N-glycolylneuraminic acid (Neu5Gc). However, after enzootic transmission in chickens, the viruses exclusively bind to Neu5Ac. The absence of Neu5Gc expression in gallinaceous poultry, particularly chickens, exerts selective pressure, shaping IAV populations, and promoting the acquisition of adaptive amino acid substitutions in the hemagglutinin protein. This results in the loss of Neu5Gc binding and an increase in virus transmissibility in gallinaceous poultry, particularly chickens. Consequently, the transmission capability of these poultry-adapted H7 IAVs in wild water birds decreases. Timely intervention, such as stamping out, may help reduce virus adaptation to domestic chicken populations and lower the risk of enzootic outbreaks, including those caused by IAVs exhibiting high pathogenicity.

Mixture and Non-Mixture Cure Models for the survival analysis of SARS-CoV-2 patients in Khyber Pakhtunkhwa, Pakistan.

To examine the potential difference in survival and risk of death between asymptomatic and symptomatic SARS-CoV-2 patients, controlled by age and gender for all the attendance in hospitals of Khyber Pakhtunkhwa (KP), Pakistan. In this retrospective study, the medical records of 6273 SARS-CoV-2 patients admitted to almost all hospitals in Khyber Pakhtunkhwa during the first wave of the coronavirus outbreak from March to June 2020 were analysed. The effects of gender, age, and being symptomatic on the survival of SARS-CoV-2 patients were assessed using cure-survival models as opposed to the conventional Cox proportional hazards model. The prevalence of initially symptomatic patients was 55.8%, and the overall mortality rate was 11.8%. The fitted cure-survival models suggest that age affects the probability of death (incidence) but not the short-term survival time of patients (latency); symptomatic patients have a higher risk of death than their asymptomatic counterparts, but the survival time of symptomatic patients is longer on average; gender has no significant effect on the probability of death and survival time. The available data and statistical results suggest that asymptomatic and young patients are generally less susceptible to initial infection with SARS-CoV-2 and therefore have a lower risk of death. Our regression models show that uncured asymptomatic patients generally have poorer short-term survival than their uncured symptomatic counterparts. The association between gender and survival outcome was not significant.

Surviving the storm: Wave-wise comparison of the pandemic's impact on mental health dynamics, sleep patterns, and preventive behaviors among coronavirus patients in Northern India.

Different clinical manifestations were revealed by the distinct waves of the coronavirus. The pandemic had a multifaceted impact on mental health, sleep patterns, and associated fear. It was an observational online survey using by using Google Forms in the city of Chandigarh between April 2020 and April 2021 across three waves of the coronavirus outbreak (first wave from March 2020 to May 2020, second wave from June 2020 to January 2021, and third wave from February 2021 to April 2021). Fear of coronavirus disease (COVID), preventive behaviors, insomnia-related problems, and impact of the event were assessed by using standardized scales. The participants who were infected during the first phase exhibited significantly higher levels of distress, loss of control over their reactions, increased fear of coronavirus and sleep problems, and also greater adherence to preventive behaviors compared to those who were infected during the second and third waves. A tendency to emerge post-traumatic stress disorder (PTSD) was seen in 68 (58.1%) of the participants (Peritraumatic Distress Inventory (PDI) score >14) and 34 (29.1%) of all the participants (PDI score >23). Overall, 66 (56.4%) participants reported having insomnia. About 24 people (20.5%) had clinical concerns about PTSD, 20 people (17.1%) had probable PTSD diagnoses, and 16 people (13.7%) experienced a severe coronavirus disease 2019 (COVID-19) pandemic impact on their lives. The first wave of COVID-19 had a greater psychological impact than subsequent waves. Further research must fill important gaps in our knowledge of the clinical range and long-term effects.

Forecasting infectious diseases in Brazilian cities: Integrating socio-economic and geographic data from related cities through a machine learning approach

Supervised machine learning models and public surveillance data have been employed for infectious disease forecasting in many settings. These models leverage various data sources capturing drivers of disease spread, such as climate conditions or human behavior. However, few models have incorporated the organizational structure of different geographic locations for forecasting. Traveling waves of seasonal outbreaks have been reported for dengue, influenza, and other infectious diseases, and many of the drivers of infectious disease dynamics may be shared across different cities, either due to their geographic or socioeconomic proximity. In this study, we developed a machine learning model to predict case counts of four infectious diseases across Brazilian cities one week ahead by incorporating information from related cities. We compared selecting related cities using both geographic distance and GDP per capita. Incorporating information from geographically proximate cities improved predictive performance for two of the four diseases, specifically COVID-19 and Zika. We also discuss the impact on forecasts in the presence of anomalous contagion patterns and the limitations of the proposed methodology.

Comparative Evaluation of Different Antivirals against Lumpy Skin Disease in Cattle

India is facing a new wave of Lumpy skin disease outbreaks since May 2022, spreading in more than 22 states and causing morbidity to more than 29 lakh animals and mortality to more than 2 lakh animals. Lack of specific antiviral treatment restores symptomatic therapeutic interventions. However, in the advent of large no. of cases and severity of disease, investigations on specific antiviral drugs are imperative. This scientific study was conducted on a group of LSD-affected cattle (N = 40) from the trans-Himalayan region of Kashmir (Jammu and Kashmir). The affected cattle were subjected to different treatments, including acyclovir (n = 27), symptomatic treatment (n = 7), and ivermectin (n = 6), along with supportive drugs. The animals were carefully monitored and compared both within and between groups at various intervals (0-96 hr) using a two-way analysis of variance (ANOVA). Significant (P ≤ 0.05) improvement in regaining rectal temperature, respiration rate, and heart rate was noted 48 hours after treatment in a group of LSD-affected animals (N = 27) treated with acyclovir at a dose rate of 1 mg/kg body weight (small cattle) to 1.5 mg/kg (large cattle) intravenously in 500 ml normal saline along with supportive drugs including enrofloxacin (2.5 mg/kg), combination of meloxicam (0.25 mg/kg) and paracetamol (7.5 mg/kg) and pheniramine maleate (0.5 mg/kg) all intramuscularly, compared to group of LSD affected cattle (N = 6) treated with ivermectin (0.2 mg/kg subcutaneously) and supportive drugs and another group of LSD affected cattle (N = 7) treated symptomatically with only supportive drugs. Acyclovir treated group showed a significant (P ≤ 0.05) decrease in total leucocyte count, lymphocyte, and basophil count from 0 hour to 96 hour of treatment (23.00 ± 0.534 to 5.59 ± 0.208; 13.97 ± 0.310 to 3.43 ± 0.126; 0.11 ± 0.003 to 0.03 ± 0.001 respectively). Significant (P ≤ 0.05) decrease in total oxidative status (TOS: 73.31%) and increase in total antioxidant status (TAS: 59.9%) was observed in acyclovir treated group followed by ivermectin treated group (TOS: 68.05% and TAS: 27.16%) compared to symptomatically treated group (TOS: 42.41% and TAS: 18.75%). Acyclovir being comparatively more specific antiviral agent than ivermectin may have helped in amelioration of clinical severity and regaining of normal physiological, hematological, and oxidative indices in LSD-affected animals. The current study demonstrates expedited recovery, diminished clinical severity, and re-establishment of physiological, hematological and oxidative markers in animals subjected to acyclovir treatment, followed by animals administered with ivermectin, when compared to animals receiving symptomatic treatment. However, further studies are required to investigate safety or adverse effects, if any.

Dual-Lumen Extracorporeal Membrane Oxygenation Cannulation Technique Using Only Transthoracic Echocardiography - A Case Series.

Bicaval dual lumen cannula (DLC) is gaining popularity in veno-venous extracorporeal membrane oxygenation (V-V ECMO) for having less recirculation and facilitating mobilization. It is usually inserted under fluoroscopic or transesophageal echocardiographic guidance to prevent potentially fatal complications. Thus, their utilization was limited during the COVID-19 outbreak due to stringent quarantine policy and manpower shortage, especially when emergency insertion was required. To describe our experience on DLC insertion using transthoracic echocardiography alone during the pandemic, with a focus on safety considerations by using detail step-by-step procedural guide. Four patients were performed V-V ECMO using the transthoracic echocardiographic-guided DLC cannulation technique during the fifth wave of the COVID-19 outbreak, with no cannulation-related complications. Transthoracic echocardiographic guidance for DLC insertion is feasible and probably safe with a detailed guide, which can be adopted as a supplementary tool during future endemic outbreaks.

THE POST PANDEMIC CHALLENGES AND ECONOMIC RECOVERY OF SOUTH ASIAN NATIONS

The global economic recovery is facing a major challenge amid pressures such as new divergent waves of covid-19 disease outbreaks, continuing labor force challenges, persistent supply chain challenges and rising inflation. South Asian countries have maintained the pace of their economic recovery amid robust remittances and broadly supportive policy stances. Estimated at 7.4 percent in 2021, Asia's GDP is expected to expand at an average pace of 5.9 percent in 2022. However, South Asia's economic recovery is still weak and uneven. Fiscal policy remains highly restrictive, making it more challenging to a sustained recovery in economic activity and increase employment. As far as India is concerned, economic recovery is on a solid path amid a rapid vaccine easing social restrictions and supportive fiscal stance.

Psychological factors promote the habituation effect on social workers' posttraumatic stress disorder symptoms after repeated COVID-19 outbreaks.

The present study investigates whether psychological factors influence the habituation or sensitization effect during repeated COVID-19 outbreaks. A total of 838 social workers from districts affected by different waves of COVID-19 outbreaks (two waves, n = 387; one wave, n = 177; zero waves, n = 274) reported their posttraumatic stress disorder (PTSD) symptoms, psychological security, emotional regulation, resilience, spiritual health, and social support (December 2021). The rate of PTSD among social workers stands at 34% (cutoff point 38). Social workers developed a habituation response amid the ongoing pandemic, with individuals who encountered a higher number of COVID-19 outbreaks exhibiting fewer symptoms of PTSD (F = 3.04, p < .05, η² = 0.007). Social workers who experienced two outbreaks had significantly lower PTSD symptoms than those who did not experience any (p = .018, 95% CI [0.431, 4.635]). A bootstrapped multiple mediation analysis indicates that psychological security (indirect effect: β = -0.590, 95% CI [-0.989, -0.192]) and emotional regulation (indirect effect: β = -0.474, 95% CI [-0.899, -0.069]) completely mediate the association between outbreaks of COVID-19 and PTSD symptoms. The incidence of PTSD symptoms was high in social workers. Chinese social workers underwent a habituation effect after repeated outbreaks of COVID-19. Improving psychological security and emotional regulation can reduce PTSD symptoms due to the repeated outbreak of COVID-19 among the public. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Neuroradiological manifestations in hospitalized patients with COVID-19: An Italian national multicenter study on behalf of AINR (Associazione Italiana di Neuroradiologia) and SIRM (Società Italiana di Radiologia Medica).

This multicentric study aims to characterize and assess the occurrence of neuroradiological findings among patients with SARS-CoV-2 infection during the first Italian wave of the pandemic outbreak. Patients' data were collected between May 2020 and June 2020. Clinical and laboratory data, chest imaging, brain CT, and MRI imaging were included. Acquired data were centralized and analyzed in two hospitals: ASST Spedali Civili, Brescia, and IRRCS San Raffaele Research Hospital, Milan, Italy. COVID-19 patients were classified into two different subgroups, vascular and nonvascular. The vascular pattern was further divided into ischemic and hemorrhagic stroke groups. Four hundred and fifteen patients from 20 different Italian Centers were enrolled in the study. The most frequent symptom was focal neurological deficit, found in 143 patients (34.5%). The most frequent neuroradiological finding was ischemic stroke in 122 (29.4%) patients. Forty-four (10.6%) patients presented a cerebral hemorrhage. Forty-seven patients had non-stroke neuroimaging lesions (11.3%). The most common was PRES-like syndrome (28%), SWI hypointensities (22%), and encephalitis (19%). The stroke group had higher CAD risk (37.5% vs 20%, p = .016) and higher D-dimer levels (1875ng/mL vs 451ng/mL, p < .001) compared to the negative group. Our study describes the biggest cohort study in Italy on brain imaging of COVID-19 patients and confirms that COVID-19 patients are at risk of strokes, possibly due to a pro-thrombotic microenvironment. Moreover, apart from stroke, the other neuroradiological patterns described align with the ones reported worldwide.

University Students' Vaccination Intention after the Fifth Wave of the COVID-19 Outbreak in Hong Kong: Inspiration from a Health Belief Model.

The fifth wave of COVID-19, driven by the Omicron variant, started to surge in Hong Kong in December 2021. Previous studies have shown that younger adults, compared to older adults, are vulnerable to increased risks of side effects after vaccination. However, little is known about the COVID-19 vaccination behavior among younger adults, especially university students, in Hong Kong. Therefore, the present online survey study aimed to investigate the predictors of COVID-19 vaccination intention among university students in Hong Kong using the Health Belief Model (HBM) as a framework. Two other potential predictors, the previous influenza vaccine uptake frequency and the Hong Kong SAR government vaccination lottery program, were also examined. The intention to receive another dose of the COVID-19 vaccine was low (36.4%). Multivariate binomial logistic regression analysis showed that, after controlling for demographic and baseline characteristics, the perceived susceptibility (OR = 2.98, CI = 1.18-7.53) and previous influenza vaccine uptake frequency (OR = 1.54, CI = 1.08-2.19) significantly and positively predicted the COVID-19 vaccination intention. However, the government vaccination lottery program (i.e., wining prizes for being vaccinated) (OR = 0.87, CI = 0.34-2.26) was not a significant motivator of COVID-19 vaccination. Future public health campaigns should focus on the individual susceptibility to COVID-19 and past influenza vaccination history to promote increased vaccination uptake among university students.

EDNA monitoring detects new outbreak wave of corallivorous seastar (Acanthaster cf. solaris) at Lizard Island, Great Barrier Reef

Crown-of-thorns seastar (CoTS, Acanthaster cf. solaris) outbreaks remain a significant cause of coral loss on the Great Barrier Reef (GBR) and across the West-Pacific Ocean. Previous outbreaks on the GBR have only been discovered once fully established, which constrains opportunities for effective control. Early detection of outbreaks would provide an important opportunity for early intervention and increase understanding of outbreak cause(s). Here, we assess the utility of environmental DNA (eDNA) monitoring to detect the initiation of a population outbreak at Lizard Island over five years (2019–2023), compared with density estimates obtained using Scooter-Assisted Large Area Diver-based (SALAD) surveys. At each of the five eDNA sampling sites, 30 replicate samples were collected annually and analysed with CoTS-specific primer sets and digital droplet PCR. Both methods detected distinct increases in CoTS densities from 2020/21 onwards, indicating the start of a new population outbreak. A large part of the observed variation in eDNA (expressed as the percentage of positive samples) was explained by changes in recorded CoTS density, confirming that eDNA data provide a quantitative estimate for adult CoTS abundance. SALAD surveys and eDNA are new and complementary monitoring methods that facilitate early detection of CoTS outbreaks, which will enable more effective management intervention.

Regional and temporal variations in COVID-19 cases and deaths in Ethiopia: Lessons learned from the COVID-19 enhanced surveillance and response.

The COVID-19 pandemic is one of the most devastating public health emergencies of international concern to have occurred in the past century. To ensure a safe, scalable, and sustainable response, it is imperative to understand the burden of disease, epidemiological trends, and responses to activities that have already been implemented. We aimed to analyze how COVID-19 tests, cases, and deaths varied by time and region in the general population and healthcare workers (HCWs) in Ethiopia. COVID-19 data were captured between October 01, 2021, and September 30, 2022, in 64 systematically selected health facilities throughout Ethiopia. The number of health facilities included in the study was proportionally allocated to the regional states of Ethiopia. Data were captured by standardized tools and formats. Analysis of COVID-19 testing performed, cases detected, and deaths registered by region and time was carried out. We analyzed 215,024 individuals' data that were captured through COVID-19 surveillance in Ethiopia. Of the 215,024 total tests, 18,964 COVID-19 cases (8.8%, 95% CI: 8.7%- 9.0%) were identified and 534 (2.8%, 95% CI: 2.6%- 3.1%) were deceased. The positivity rate ranged from 1% in the Afar region to 15% in the Sidama region. Eight (1.2%, 95% CI: 0.4%- 2.0%) HCWs died out of 664 infected HCWs, of which 81.5% were from Addis Ababa. Three waves of outbreaks were detected during the analysis period, with the highest positivity rate of 35% during the Omicron period and the highest rate of ICU beds and mechanical ventilators (38%) occupied by COVID-19 patients during the Delta period. The temporal and regional variations in COVID-19 cases and deaths in Ethiopia underscore the need for concerted efforts to address the disparities in the COVID-19 surveillance and response system. These lessons should be critically considered during the integration of the COVID-19 surveillance system into the routine surveillance system.

Prevalence and risk factors of cytomegalovirus reactivation in critically Ill patients with COVID-19 pneumonia.

In critically ill patients with COVID-19, secondary infections are potentially life-threatening complications. This study aimed to determine the prevalence, clinical characteristics, and risk factors of CMV reactivation among critically ill immunocompetent patients with COVID-19 pneumonia. A retrospective cohort study was conducted among adult patients who were admitted to ICU and screened for quantitative real-time PCR for CMV viral load in a tertiary-care hospital during the third wave of the COVID-19 outbreak in Thailand. Cox regression models were used to identify significant risk factors for developing CMV reactivation. A total of 185 patients were studied; 133 patients (71.9%) in the non-CMV group and 52 patients (28.1%) in the CMV group. Of all, the mean age was 64.7±13.3 years and 101 patients (54.6%) were males. The CMV group had received a significantly higher median cumulative dose of corticosteroids than the non-CMV group (301 vs 177 mg of dexamethasone, p<0.001). Other modalities of treatments for COVID-19 including anti-viral drugs, anti-cytokine drugs and hemoperfusion were not different between the two groups (p>0.05). The 90-day mortality rate for all patients was 29.1%, with a significant difference between the CMV group and the non-CMV group (42.3% vs. 24.1%, p = 0.014). Median length of stay was longer in the CMV group than non-CMV group (43 vs 24 days, p<0.001). The CMV group has detectable CMV DNA load with a median [IQR] of 4,977 [1,365-14,742] IU/mL and 24,570 [3,703-106,642] in plasma and bronchoalveolar fluid, respectively. In multivariate analysis, only a cumulative corticosteroids dose of dexamethasone ≥250 mg (HR = 2.042; 95%CI, 1.130-3.688; p = 0.018) was associated with developing CMV reactivation. In critically ill COVID-19 patients, CMV reactivation is frequent and a high cumulative corticosteroids dose is a significant risk factor for CMV reactivation, which is associated with poor outcomes. Further prospective studies are warranted to determine optimal management.

Characterization of antibody response to SARS-CoV-2 Orf8 from three waves of COVID-19 outbreak in Thailand.

A dynamic of virus adaptation and a mass vaccination campaign could significantly reduce the severity of clinical manifestations of COVID-19 and transmission. Hence, COVID-19 may become an endemic disease globally. Moreover, mass infection as the COVID-19 pandemic progressed affected the serology of the patients as a result of virus mutation and vaccination. Therefore, a need exists to acquire accurate serological testing to monitor the emergence of new outbreaks of COVID-19 to promptly prevent and control the disease spreading. In this study, the anti-Orf8 antibodies among samples collected in Thailand's first, fourth, and fifth waves of COVID-19 outbreaks compared with pre-epidemic sera were determined by indirect ELISA. The diagnostic sensitivity and specificity of the anti-Orf8 IgG ELISA for COVID-19 samples from the first, fourth, and fifth waves of outbreaks was found to be 100% compared with pre-epidemic sera. However, the diagnostic sensitivity and specificity of the anti-Orf8 IgG ELISA for a larger number of patient samples and controls from the fifth wave of outbreaks which were collected on day 7 and 14 after an RT-PCR positive result were 58.79 and 58.44% and 89.19 and 58.44%, respectively. Our data indicated that some of the controls might have antibodies from natural past infections. Our study highlighted the potential utility of anti-Orf8 IgG antibody testing for seroprevalence surveys but still warrants further investigations.

Wastewater surveillance together with metaviromic data revealed the unusual resurgence of infectious diseases after the first wave of the COVID-19 outbreak

How to address public health priorities after COVID-19 is becoming a critical task. To this end, we conducted wastewater surveillance for six leading pathogens, namely, SARS-CoV-2, norovirus, rotavirus, influenza A virus (IAV), enteroviruses and respiratory syncytial virus (RSV), in Nanchang city from January to April 2023. Metaviromic sequencing was conducted at the 1st, 4th, 7th, 9th, 12th and 14th weeks to reveal the dynamics of viral pathogens that were not covered by qPCR. Amplicon sequencing of the conserved region of norovirus GI and GII and the rotavirus and region encoding nonstructural protein of RSV was also conducted weekly. The results showed that after a rapid decrease in SARS-CoV-2 sewage concentrations occurred in January 2023, surges of norovirus, rotavirus, IAV and RSV started at the 6th, 7th, 8th and 11th weeks, respectively. The dynamics of the sewage concentrations of norovirus, rotavirus, IAV and RSV were consistent with the off-season resurgence of the above infectious diseases. Notably, peak sewage concentrations of norovirus GI, GII, rotavirus, IAV and RSV were found at the 6th, 3rd, 7th, 7th and 8th weeks, respectively. Astroviruses also resurge after the 7th week, as revealed by metaviromic data, suggesting that wastewater surveillance together with metaviromic data provides an essential early warning tool for revealing patterns of infectious disease resurgence.