Number Of Coronavirus Disease 2019 Cases Research Articles

Phylogenetic analysis of SARS-CoV-2 lineage development across the first and second waves in Eastern Germany in 2020: insights into the cause of the second wave.

In Germany, Eastern regions had a mild first wave of coronavirus disease 2019 (COVID-19) from March to May 2020, but were badly hit by a second wave later in autumn and winter. It is unknown how the second wave was initiated and developed in Eastern Germany where the number of COVID-19 cases was close to zero in June and July 2020. We used genomic epidemiology to investigate the dynamic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage development across the first and second waves in Eastern Germany. With detailed phylogenetic analyses we could show that SARS-CoV-2 lineages prevalent in the first and second waves in Eastern Germany were different, with several new variants including four predominant lineages in the second wave, having been introduced into Eastern Germany between August and October 2020. The results indicate that the major driving force behind the second wave was the introduction of new variants.

Comparison of ARIMA, ES, GRNN and ARIMA–GRNN hybrid models to forecast the second wave of COVID-19 in India and the United States

Abstract As acute infectious pneumonia, the coronavirus disease-2019 (COVID-19) has created unique challenges for each nation and region. Both India and the United States (US) have experienced a second outbreak, resulting in a severe disease burden. The study aimed to develop optimal models to predict the daily new cases, in order to help to develop public health strategies. The autoregressive integrated moving average (ARIMA) models, generalised regression neural network (GRNN) models, ARIMA–GRNN hybrid model and exponential smoothing (ES) model were used to fit the daily new cases. The performances were evaluated by minimum mean absolute per cent error (MAPE). The predictive value with ARIMA (3, 1, 3) (1, 1, 1)14 model was closest to the actual value in India, while the ARIMA–GRNN presented a better performance in the US. According to the models, the number of daily new COVID-19 cases in India continued to decrease after 27 May 2021. In conclusion, the ARIMA model presented to be the best-fit model in forecasting daily COVID-19 new cases in India, and the ARIMA–GRNN hybrid model had the best prediction performance in the US. The appropriate model should be selected for different regions in predicting daily new cases. The results can shed light on understanding the trends of the outbreak and giving ideas of the epidemiological stage of these regions.

Trend Analysis and Intervention Effect Starting Point Detection of COVID-19 Epidemics Using Recalibrated Time Series Models - Worldwide, 2020.

Objective: This study aimed to identify a model for short-term coronavirus disease 2019 (COVID-19) trend prediction and intervention evaluation. Methods: We compared the autoregressive integrated moving average (ARIMA) model and Holt exponential smoothing (Holt) model on predicting the number of cumulative COVID-19 cases in China. Based on the mean absolute percentage error (MAPE) value, the optimal model was selected and further tested using data from the United States, Italy and Republic of Korea. The intervention effect starting time points and abnormal trend changes were detected by observing the pattern of differences between the predicted and real trends. Results: The recalibrated ARIMA model with a 5-day prediction time span has the best model performance with MAPEs ranged between 2% and 5%. The intervention effects started to show on February 7 in the mainland of China, March 5 in Republic of Korea and April 27 in Italy, but have not been detected in the US as of May 19. Temporary abnormal trends were detected in Korea and Italy, but the overall epidemic trends were stable since the effect starting points. Conclusion: The recalibrated ARIMA model can detect the intervention effects starting points and abnormal trend changes; thus to provide valuable information support for epidemic trend analysis and intervention evaluation.

The Multifaceted Impact of COVID-19 Pandemic on Dentists in Tamil Nadu, India: A Qualitative Study

Introduction: India has become the Coronavirus Disease 2019 (COVID-19) epicentre with the highest number of COVID-19 cases being reported each day. This has caused a major impact on healthcare workers including dentists across the country. Most dental clinics in Tamil Nadu were closed during the initial two months of draconian lockdown enforced by the Government of India (GOI). As partial lockdown measures were introduced over the subsequent months, dental clinics have started functioning and receiving patients for emergency dental treatment. Aim: This study was done among dentists practicing in Tamil Nadu amidst the COVID-19 pandemic to understand how the pandemic has impacted their professional and personal lives. Materials and Methods: A qualitative study using online focus group discussion was conducted among 32 dentists practicing in Tamil Nadu, India using a structured interview guide in the month of July 2020. After data collection, the focus group discussions were transcribed manually and an inductive thematic analysis was performed using Braun and Clarke’s six phases for thematic analysis. Results: Three major themes were identified after the thematic analysis namely limitations of off-campus distance learning, challenges faced in dental practice during the COVID-19 pandemic and social life impacts of COVID-19 among dentists. Conclusion: Dentists in this study felt that the COVID-19 pandemic was negatively impacting their dental practices owing to lack of clarity in COVID-19 protocols, lack of patient awareness, high cost of Personal Protective Equipment (PPE), increasing overhead expenses, ergonomic difficulties in treating patients while wearing PPE, patients’ unwillingness to pay higher charges for treatment under COVID-19 protocols and fear of contracting COVID-19. Majority of participants in this study did not report any negative impacts of social isolation as many of them had stayed with their families during the lockdown.

Predicting COVID-19 confirmed cases in New York and DKI Jakarta by nonlinear fitting of a Bose–Einstein energy distribution and its implications on social restrictions

ObjectiveGlobal society pays huge economic toll and live loss due to COVID-19 (Coronavirus Disease 2019) pandemic. In order to have a better management of this pandemic, many institutions develop their own models to predict number of COVID-19 cases, hospitalizations and mortalities. These models, however, are shown to be unreliable and need to be revised on a daily basis. MethodsHere, we develop a Bose–Einstein (BE)-based statistical model to predict daily COVID-19 cases up to 14 days in advance. This fat-tailed model is chosen based on three reasons. First, it contains a peak and decaying phase. Second, it also has both accelerated and decelerated phases which are similarly observed in an epidemic curve. Third, the shape of both the BE energy distribution and the epidemic curve is controlled by a set of parameters. The BE model daily predictions are then verified against simulated data and confirmed COVID-19 daily cases from two epidemic centres, i.e. New York and DKI Jakarta. ResultOver- predictions occur at the earlier stage of the epidemic for all data sets. Models parameters for both simulated and New York data converge to a certain value only at the latest stage of the epidemic progress. At this stage, model's skill is high for both simulated and New York data, i.e. the predictability is greater than 80% with decreasing RMSE. On the other hand, at that stage, the DKI's model's predictability is still fluctuating with increasing RMSE. ConclusionThis implies that New York could leave the stay-at-home order, but DKI Jakarta should continue its large-scale social restriction order. There remains a great challenge in predicting the full course of an epidemic using small data collected during the earlier phase of the epidemic.

Estimation of case-fatality rate in COVID-19 patients with hypertension and diabetes mellitus in the New York state: a preliminary report.

Pre-existing health conditions may exacerbate the severity of coronavirus disease 2019 (COVID-19). We aimed to estimate the case-fatality rate (CFR) and rate ratios (RR) for patients with hypertension (HBP) and diabetes mellitus (DM) in the New York state. We obtained the age-specific number of COVID-19 confirmed cases and deaths from public reports provided by the New York State Department of Health, and age-specific prevalence of HBP and DM from the Behavioral Risk Factor Surveillance System 2017. We calculated CFR and RR for COVID-19 patients with HBP and DM based on the reported number of deaths with the comorbidity divided by the expected number of COVID-19 cases with the comorbidity. We performed subgroup analysis by age and calculated the CFR and RR for ages of 18-44, 45-64 and 65+ years, respectively. We found that the older population had a higher CFR, but the elevated RRs associated with comorbidities are more pronounced among the younger population. Our findings suggest that besides the elderly, the young population with comorbidity should also be considered as a vulnerable group.

Impact of COVID-19 Comorbidities on Pregnant Mothers

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Common symptoms that occur in pregnant mothers with COVID-19 include fever, cough, shortness of breath, and diarrhea. Currently, SARS-CoV-2 has mutated and based on facts it is also shown that number of COVID-19 cases increasing. Increase in number of COVID-19 cases associated with the emergence of a new variant of SARS-CoV-2 due to mutation. Furthermore, the severity of COVID-19 patients is influenced by comorbidity of COVID-19 . The three major comorbidity of COVID-19 that affects the severity of COVID-19 patients are diabetes mellitus, hypertension and heart disease. For general community who have comorbidity of COVID-19, especially diabetes mellitus, hypertension and or heart disease (top three comorbidity of COVID-19) should still be careful and have a healthy lifestyle, keep adhering to health protocols so that they are not infected with SARS-CoV-2, and not suffering of COVID-19. The invitation to avoid COVID-19 is intended for anyone, including mothers, especially pregnant mothers who have comorbidity of COVID-19.

New York City Vascular Surgeons during the COVID-19 Pandemic.

The coronavirus disease 2019 (COVID-19) pandemic has forever changed the lives of many across the world. Like many others, New Yorkers witnessed their hospital systems become overwhelmed with a massive influx of critically ill patients. Protocols, workflow, staffing, and individual responsibilities all changed as health care providers scrambled to help where they could. As we see, for the second time this year, a rapid rise in the number of COVID-19 cases in the United States, I wanted to share our experience as vascular surgeons during the first surge from a health care system located in New York City, one of the largest epicenters of the pandemic.

Strong Correlation between the Case Fatality Rate of COVID-19 and the rs6598045 Single Nucleotide Polymorphism (SNP) of the Interferon-Induced Transmembrane Protein 3 (IFITM3) Gene at the Population-Level.

Coronavirus disease 2019 (COVID-19) is a fatal pandemic disease that is caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As of 13 December, 2020, over 70,000,000 cases and 1,500,000 deaths have been reported over a period of several months; however, the mechanism underlying the pathogenesis of COVID-19 has not been elucidated. To identify the novel risk genetic biomarker for COVID-19, we evaluated the correlation between the case fatality rate of COVID-19 and the genetic polymorphisms of several potential COVID-19-related genes, including interferon-induced transmembrane protein 3 (IFITM3), the angiotensin I converting enzyme 2 (ACE2) gene, transmembrane protease, serine 2 (TMPRSS2), interleukin 6 (IL6), leucine zipper transcription factor-like protein 1 (LZTFL1), and the ABO genes, in various ethnic groups. We obtained the number of COVID-19 cases and deaths from the World Health Organization (WHO) COVID-19 dashboard and calculated the case fatality rate of each ethnic group. In addition, we obtained the allele distribution of the polymorphisms of the IFITM3, ACE2, TMPRSS2, IL6, LZTFL1, and ABO genes from the 1000 Genomes Project and performed Log-linear regression analysis using SAS version 9.4. We found different COVID-19 case fatality rates in each ethnic group. Notably, we identified a strong correlation between the case fatality rate of COVID-19 and the allele frequency of the rs6598045 single nucleotide polymorphism (SNP) of the IFITM3 gene. To the best of our knowledge, this report is the first to describe a strong correlation between the COVID-19 case fatality rate and the rs6598045 SNP of the IFITM3 gene at the population-level.

The Impact of the COVID-19 Epidemic on Older Adults in Rural and Urban Areas in Mexico.

ObjectivesMexico is among the countries in Latin America hit hardest by coronavirus disease 2019 (COVID-19). A large proportion of older adults in Mexico have high prevalence of multimorbidity and live in poverty with limited access to health care services. These statistics are even higher among adults living in rural areas, which suggest that older adults in rural communities may be more susceptible to COVID-19. The objectives of the article were to compare clinical and demographic characteristics for people diagnosed with COVID-19 by age group, and to describe cases and mortality in rural and urban communities.MethodWe linked publicly available data from the Mexican Ministry of Health and the Census. Municipalities were classified based on population as rural (<2,500), semirural (≥2,500 and <15,000), semiurban (≥15,000 and <100,000), and urban (≥100,000). Zero-inflated negative binomial models were performed to calculate the total number of COVID-19 cases, and deaths per 1,000,000 persons using the population of each municipality as a denominator.ResultsOlder adults were more likely to be hospitalized and reported severe cases, with higher mortality rates. In addition, rural municipalities reported a higher number of COVID-19 cases and mortality related to COVID-19 per million than urban municipalities. The adjusted absolute difference in COVID-19 cases was 912.7 per million (95% confidence interval [CI]: 79.0–1746.4) and mortality related to COVID-19 was 390.6 per million (95% CI: 204.5–576.7).DiscussionUrgent policy efforts are needed to mandate the use of face masks, encourage handwashing, and improve specialty care for Mexicans in rural areas.

Genomic epidemiology reveals multiple introductions of SARS-CoV-2 from mainland Europe into Scotland.

Coronavirus disease 2019 (COVID-19) was first diagnosed in Scotland on 1 March 2020. During the first month of the outbreak, 2,641 cases of COVID-19 led to 1,832 hospital admissions, 207 intensive care admissions and 126 deaths. We aimed to identify the source and number of introductions of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into Scotland using a combined phylogenetic and epidemiological approach. Sequencing of 1,314 SARS-CoV-2 viral genomes from available patient samples enabled us to estimate that SARS-CoV-2 was introduced to Scotland on at least 283 occasions during February and March 2020. Epidemiological analysis confirmed that early introductions of SARS-CoV-2 originated from mainland Europe (the majority from Italy and Spain). We identified subsequent early outbreaks in the community, within healthcare facilities and at an international conference. Community transmission occurred after 2 March, 3 weeks before control measures were introduced. Earlier travel restrictions or quarantine measures, both locally and internationally, would have reduced the number of COVID-19 cases in Scotland. The risk of multiple reintroduction events in future waves of infection remains high in the absence of population immunity.

COVID-19 and Pulmonary Hypertension in Children: What Do We Know So Far?

The interplay between coronavirus disease 2019 (COVID-19) and pulmonary hypertension (PH) in children is unknown. Adults with PH are at potential risk for severe complications and high mortality due to associated comorbidities. It is difficult to extrapolate the outcomes of COVID-19 in adults to pediatric PH patients. Overall, a small number of COVID-19 cases is reported in patients with preexisting PH. Several factors may be responsible for the low incidence of COVID-19 in children with PH. Pulmonary hypertension is a rare disease, testing is not universal, and patients may have followed more rigorously the Center for Disease Control’s guidelines recommended for personal protection with mask-wearing, social distancing, and hand sanitization through ongoing health education. The small number of COVID-19 cases in patients with preexisting PH does not support that PH is protective for COVID-19. However, medications used to treat PH may have some protection against COVID-19. This review discusses the pathophysiology of PH occurring with COVID-19, differences between children and adults with COVID-19, strategies for management of preexisting PH in children during the ongoing pandemic, and its impact within the field of PH.

Efficient detection of SARS-CoV-2 RNA in the solid fraction of wastewater

In the context of the coronavirus disease 2019 (COVID-19) pandemic, environmental surveillance for the detection of SARS-CoV-2 has become increasingly important. Studies have demonstrated that the SARS-CoV-2 RNA is present in the feces of infected individuals; further, its presence in wastewater has been reported. However, an optimized method for its detection in sewage has not yet been adequately investigated. Therefore, in this study, the efficient detection of SARS-CoV-2 RNA in the solid fraction of wastewater was investigated using two quantitative PCR assays. In particular, wastewater samples were collected from a manhole located in the commercial district of a metropolitan region in Japan, where COVID-19 is highly prevalent, and two wastewater treatment plants (WWTPs). The samples were concentrated using four separate methods, namely, electronegative membrane adsorption, polyethylene glycol precipitation, ultrafiltration, and solid precipitation. Each method revealed a significant concentration of pepper mild mottle virus (PMMoV) RNA, which is an indicator virus for wastewater. As expected, non-enveloped PMMoV RNA was enriched in the supernatant fraction such that relatively low concentrations were detected in the solid fraction of the wastewater samples. In contrast, higher SARS-CoV-2 RNA concentrations were consistently detected in the solid fractions compared with the supernatant fractions based on the other methods that were investigated in this study. Spearman's correlation tests showed that the SARS-CoV-2 RNA concentrations in wastewater samples from the WWTP were significantly correlated with the number of COVID-19 cases recorded during the data collection period. These results demonstrate that viral recovery from the solid fraction is an effective method for SARS-CoV-2 RNA surveillance in an aqueous environment.

Effect of evacuation of Japanese residents from Wuhan, China, on preventing transmission of novel coronavirus infection: A modelling study

IntroductionIn late January 2020, the Japanese government carried out three evacuations by aircraft from Wuhan, China, to avoid further cases of coronavirus disease 2019 (COVID-19) among Wuhan's Japanese residents. Evacuation by aircraft may be an effective countermeasure against outbreaks of infectious diseases, but evidence of its effect is scarce. This study estimated how many COVID-19 cases were prevented among the Japanese residents of Wuhan by the evacuation countermeasure. MethodsWe constructed a SETAIR (susceptible-exposed-transitional-asymptomatic-infectious-recovered) model to capture the epidemic growth of COVID-19 cases in Wuhan to estimate the predicted number of COVID-19 cases among Wuhan's Japanese residents if evacuation had not occurred at the end of January. We used data on the number of COVID-19 cases confirmed in Hubei Province for the period Jan 20-Feb 16, 2020, and on the number of cases of Japanese residents who were evacuated by aircraft on Jan 29, 30, and 31. ResultsEleven imported COVID-19 cases were reported on Feb 1 from among the total 566 evacuees who returned to Japan. In the case of no evacuations being made, the cumulative number of COVID-19 cases among Wuhan's Japanese residents was estimated to reach 25 (95% CI [20,29]) on Feb 8 and 34 (95% CI [28,40]) on Feb 15. A 1-week delay in the evacuation might be led to 14 additional cases and a 2-week delay to 23 additional cases. ConclusionsEvacuation by aircraft can contribute substantially to reducing the number of infected cases in the initial stage of the outbreak.

Variation in COVID-19 Diagnosis by Zip Code and Race and Ethnicity in Indiana.

Objectives: To describe variations in coronavirus disease 2019 (COVID-19) diagnosis by zip code race and ethnicity in Indiana.Methods: Cross-sectional evaluation of subjects with SARS-CoV-2 at Indiana University Health. We performed two separate analyses, first evaluating likelihood of COVID-19 diagnosis by race (Caucasian, African American, Asian, or other) and ethnicity (Hispanic vs. non-Hispanic) in the cohort encompassing the entire state of Indiana. Subsequently, patient data was geolocated with zip codes in Marion County and the immediate surrounding counties, and descriptive statistical analyses were used to calculate the number of COVID-19 cases per 10,000 persons for each of these zip codes.Results: Indiana had a total of 3,892 positive COVID-19 cases from January 1 to April 30, 2020. The odds of testing positive for COVID-19 were four-fold higher in African Americans than non-African Americans (OR 4.58, 95% CI 4.25–4.94, P < 0.0001). Increased COVID-19 cases per 10,000 persons were seen in zip codes with higher percentage of African American (median infection rate of 17.4 per 10,000 population in zip codes above median % African American compared to 6.7 per 10,000 population in zip codes below median % African American, with an overall median infection rate 9.9 per 10,000 population, P < 0.0001) or Hispanic residents (median infection rate of 15.9 per 10,000 population in zip codes above median % Hispanic compared to 7.0 per 10,000 population in zip codes below median % Hispanic, overall median infection rate 9.6 per 10,000 population, P < 0.0001).Conclusions: Individuals from zip codes with higher percentages of African American, Hispanic, foreign-born, and/or residents living in poverty are disproportionately affected by COVID-19. Urgent work is needed to understand and address the disproportionate burden of COVID-19 in minority communities and when economic disparities are present.

Asymptomatic SARS-CoV-2 infection: is it all about being refractile to innate immune sensing of viral spare-parts?-Clues from exotic animal reservoirs.

ABSTRACTA vast proportion of coronavirus disease 2019 (COVID-19) individuals remain asymptomatic and can shed severe acute respiratory syndrome (SARS-CoV) type 2 virus to transmit the infection, which also explains the exponential increase in the number of COVID-19 cases globally. Furthermore, the rate of recovery from clinical COVID-19 in certain pockets of the globe is surprisingly high. Based on published reports and available literature, here, we speculated a few immunovirological mechanisms as to why a vast majority of individuals remain asymptomatic similar to exotic animal (bats and pangolins) reservoirs that remain refractile to disease development despite carrying a huge load of diverse insidious viral species, and whether such evolutionary advantage would unveil therapeutic strategies against COVID-19 infection in humans. Understanding the unique mechanisms that exotic animal species employ to achieve viral control, as well as inflammatory regulation, appears to hold key clues to the development of therapeutic versatility against COVID-19.

WASTEWATER-BASED EPIDEMIOLOGY AS AN ALLY IN THE FIGHT AGAINST THE COVID-19: A BRIEF REVIEW

Several researchers have detected the viral genome of SARS-CoV-2 in the stools of people (symptomatic or not) diagnosed with coronavirus disease-2019 (COVID-19). In domestic wastewater, this concentration can be between 19 and 5.5 x 106 viral genomes per liter of wastewater. Wastewater-based epidemiology (WBE) starts from the premise that it is possible to estimate the number of people infected by the new coronavirus within a given population group, by analyzing the amount of viral genome present in the wastewater produced by these people. This paper presents the procedures to estimate the number of COVID-19 cases from raw wastewater samples, discusses the main aspects that involve the WBE assay and presents a discussion based on the case studies applied to COVID-19 in some countries. Finally, there is a final discussion about the current situation and the main challenges for WBE to be applied efficiently for COVID-19, as an alternative to massive human testing, especially for developing and underdeveloped countries.

Incidence of New Coronavirus Infection among Emergency Medical Services Workers

Summary. Introduction: A biological factor is the leading occupational hazard for healthcare professionals. Identification of risk factors for novel coronavirus disease 2019 (COVID-19) in ambulance employees and substantiation of measures to prevent the spread of this infection is a modern-day challenge. The purpose of our study was to examine COVID-19 incidence rates in emergency medical services (EMS) workers and to identify occupational risk factors for this infection. Materials and methods: We studied COVID-19 cases among Ryazan ambulance employees in terms of their age, sex, position, and specialty taking into account disease severity and duration for the period from May 1, 2020 to September 1, 2020. Results: We established higher relative risk values and incidence rates of the novel coronavirus infection in EMS workers compared to the population of the city of Ryazan (p &lt; 0.05). In May–August 2020, COVID-19 cases among the ambulance employees and the population of Ryazan, as well as the number of EMS-attended patients with acute respiratory infection followed a similar pattern. The number of COVID-19 cases among the staff of resuscitation crews was significantly higher than that in the general practice and other specialized crews (p &lt; 0.05). We estimated a statistically significant high relative risk of a longer and severer course of the disease among physicians compared with paramedics (RR = 1.333; p &lt; 0.05) and among EMS workers aged 61 or older (RR = 1.286; p &lt; 0.05). Conclusions: Emergency medical services workers have a high occupational risk of COVID-19 in the pandemic. Among them, employees aged 31–35 and resuscitation crewmembers face a higher risk of infection. Elderly employees aged 61–64, medical doctors, and general profile EMS workers are most at risk for a more severe and durable disease course.

Predictive Model for the Total Daily COVID-19 Cases with Herd Immunity Policy

The spread of coronavirus disease 2019 (COVID-19) has caused a pandemic, and policies for fighting COVID-19 have been enacted by the governments of most countries. The herd immunity policy is the policy that Sweden is using to fight COVID-19. The purpose of this research is to estimate the number of total COVID-19 cases in Sweden in which herd immunity is being encouraged. A logistic model was selected as the predictive model for estimating the number of COVID-19 cases in Sweden and the other Nordic countries in which the strict lockdown policy has been instigated, and a comparative study between them was conducted and validation of the predictive models was confirmed. The findings show that the herd immunity policy is applicable and acceptable but flattening the predictive curve by applying the herd immunity policy is slightly slower than when applying the strict lockdown policy.

Infection prevention and control: Key measures in healthcare settings to reduce the spread of COVID-19 pandemic

Coronavirus disease 2019 (COVID-19) pandemic is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses an enormous burden on society, economic and healthcare systems worldwide. The various measures being taken to control its spread. It has no definitive treatment and vaccination till date. Therefore, Infection Prevention and Control (IPC) practice in the healthcare facilities is the most important and essential to combat this health crisis. The increasing numbers of COVID-19 cases among healthcare professionals along with evidence of ongoing transmission in some healthcare settings suggest the gaps in the implementation of IPC practice. This need reviewing of all guidelines and their appropriate implementation. Strategic preparedness of preventive measures within health-care facilities; their proper implementation; the continuous, correct &amp; consistent performance of IPC measures and use of tools to identify IPC gaps &amp; to monitor progress are the key features to achieve success in reducing the transmission of SARS-CoV2 virus. Keywords: infection prevention and control (IPC); COVID-19; SARS-CoV-2; pandemic, hand hygiene; cleaning and disinfection