Spatial diffusion of COVID-19 in Algeria during the third wave

Evaluating the impact of testing strategies for the detection of nosocomial COVID-19 in English hospitals through data-driven modeling

Introduction

During the first wave of the COVID-19 pandemic 293,204 inpatients in England tested positive for SARS-CoV-2. It is estimated that 1% of these cases were hospital-associated using European centre for disease prevention and control (ECDC) and Public Health England (PHE) definitions. Guidelines for preventing the spread of SARS-CoV-2 in hospitals have developed over time but the effectiveness and efficiency of testing strategies for preventing nosocomial transmission has not been explored.

Methods

Using an individual-based model, parameterised using multiple datasets, we simulated the transmission of SARS-CoV-2 to patients and healthcare workers between March and August 2020 and evaluated the efficacy of different testing strategies. These strategies were: 0) Testing only symptomatic patients on admission; 1) Testing all patients on admission; 2) Testing all patients on admission and again between days 5 and 7, and 3) Testing all patients on admission, and again at days 3, and 5-7. In addition to admissions testing, patients that develop a symptomatic infection while in hospital were tested under all strategies. We evaluated the impact of testing strategy, test characteristics and hospital-related factors on the number of nosocomial patient infections.

Results

Modelling suggests that 84.6% (95% CI: 84.3, 84.7) of community-acquired and 40.8% (40.3, 41.3) of hospital-associated SARS-CoV-2 infections are detectable before a patient is discharged from hospital. Testing all patients on admission and retesting after 3 or 5 days increases the proportion of nosocomial cases detected by 9.2%. Adding discharge testing increases detection by a further 1.5% (relative increase). Increasing occupancy rates, number of beds per bay, or the proportion of admissions wrongly suspected of having COVID-19 on admission and therefore incorrectly cohorted with COVID-19 patients, increases the rate of nosocomial transmission. Over 30,000 patients in England could have been discharged while incubating a non-detected SARS-CoV-2 infection during the first wave of the COVID-19 pandemic, of which 3.3% could have been identified by discharge screening. There was no significant difference in the rates of nosocomial transmission between testing strategies or when the turnaround time of the test was increased.

Discussion

This study provides insight into the efficacy of testing strategies in a period unbiased by vaccines and variants. The findings are relevant as testing programs for SARS-CoV-2 are scaled back, and possibly if a new vaccine escaping variant emerges.

A weapon to fight against pervasive Omicron: systematic actions transiting to pre-COVID normal

The Coronavirus Disease-2019 (COVID-19) pandemic is not just a health crisis but also a social crisis. Confronted with the resurgence of variants with massive infections, the triggered activities from personal needs may promote the spread, which should be considered in risk management. Meanwhile, it is important to ensure that the policy responses on citizen life to a lower level. In the face of Omicron mutations, we need to sum up the control experience accumulated, adapting strategies in the dynamic coevolution process while balancing life resumption and pandemic control, to meet challenges of future crises. We collected 46 cases occurring between 2021 and 2022, mainly from China, but also including five relevant cases from other countries around the world. Based on case studies, we combine micro-view individual needs/behaviors with macro-view management measures linking Maslow's hierarchy of needs with the transmission chain of Omicron clusters. The proposed loophole chain could help identify both individual and management loopholes in the spread of the virus. The systematic actions that were taken have effectively combated these ubiquitous vulnerabilities at lower costs and lesser time. In the dynamic coevolution process, the Chinese government has made effective and more socially acceptable prevention policies while meeting the divergent needs of the entire society at the minimum costs. Systematic actions do help maintain the balance between individuals' satisfaction and pandemic containment. This implies that risk management policies should reasonably consider individual needs and improve the cooperation of various stakeholders with targeted flexible measures, securing both public health and life resumption.

Contact dermatitis caused by prevention measures during the COVID-19 pandemic: a narrative review

Introduction

During the outbreak of Coronavirus disease 2019 (COVID-19), health care workers wore personal protective equipment including masks, gloves and goggles for a long time. In order to reduce the transmission routes of the virus, public places were sprayed with disinfectant. Moreover, the body, hands and clothing were frequently disinfected and washed for hygiene purposes. Studies have shown that these practices could easily irritate the skin and damage the skin barrier. Long-term irritation or exposure to allergens may lead to the occurrence of contact dermatitis (CD).

Methods

Subject headings were searched via the National Library of Medicine (PubMed) and web of science databases: COVID-19; contact dermatitis; adverse skin reaction; PPE; dermatitis; mask; glory; hand hygiene, disinfection; face shield; goggle; protect cloth. A total of 246 and 646 articles were retrieved from the two databases, respectively. 402 articles remained after removing duplicates. Reviews, non-English articles, articles that could not be accessed to read or did not conform to our topic were excluded. Finally, a total of 32 cross-sectional studies, 9 case reports and 2 randomized controlled trials were included.

Discussion

This article reviews reports of CD caused by various prevention and hygiene measures during the COVID-19 pandemic. The amount of skin damage caused by COVID-19 prevention measures could be decreased by improved education about skin management.

Improved time-varying reproduction numbers using the generation interval for COVID-19

Estimating key epidemiological parameters, such as incubation period, serial interval (SI), generation interval (GI) and latent period, is essential to quantify the transmissibility and effects of various interventions of COVID-19. These key parameters play a critical role in quantifying the basic reproduction number. With the hard work of epidemiological investigators in South Korea, estimating these key parameters has become possible based on infector-infectee surveillance data of COVID-19 between February 2020 and April 2021. Herein, the mean incubation period was estimated to be 4.9 days (95% CI: 4.2, 5.7) and the mean generation interval was estimated to be 4.3 days (95% CI: 4.2, 4.4). The mean serial interval was estimated to be 4.3, with a standard deviation of 4.2. It is also revealed that the proportion of presymptomatic transmission was ~57%, which indicates the potential risk of transmission before the disease onset. We compared the time-varying reproduction number based on GI and SI and found that the time-varying reproduction number based on GI may result in a larger estimation of Rt, which refers to the COVID-19 transmission potential around the rapid increase of cases. This highlights the importance of considering presymptomatic transmission and generation intervals when estimating the time-varying reproduction number.

Epidemiological characteristics and transmission dynamics of the COVID-19 outbreak in Hohhot, China: a time-varying SQEIAHR model analysis

Background

On September 28, 2022, the first case of Omicron subvariant BF.7 was discovered among coronavirus disease 2019 (COVID-19) infections in Hohhot, China, and then the epidemic broke out on a large scale during the National Day holiday. It is imminently necessary to construct a mathematical model to investigate the transmission dynamics of COVID-19 in Hohhot.

Methods

In this study, we first investigated the epidemiological characteristics of COVID-19 cases in Hohhot, including the spatiotemporal distribution and sociodemographic distribution. Then, we proposed a time-varying Susceptible-Quarantined Susceptible-Exposed-Quarantined Exposed-Infected-Asymptomatic-Hospitalized-Removed (SQEIAHR) model to derive the epidemic curves. The next-generation matrix method was used to calculate the effective reproduction number (Re). Finally, we explored the effects of higher stringency measures on the development of the epidemic through scenario analysis.

Results

Of the 4,889 positive infected cases, the vast majority were asymptomatic and mild, mainly concentrated in central areas such as Xincheng District. People in the 30-59 age group primarily were affected by the current outbreak, accounting for 53.74%, but females and males were almost equally affected (1.03:1). Community screening (35.70%) and centralized isolation screening (26.28%) were the main ways to identify positive infected cases. Our model predicted the peak of the epidemic on October 6, 2022, the dynamic zero-COVID date on October 15, 2022, a number of peak cases of 629, and a cumulative number of infections of 4,963 (95% confidential interval (95%CI): 4,692 ~ 5,267), all four of which were highly consistent with the actual situation in Hohhot. Early in the outbreak, the basic reproduction number (R0) was approximately 7.01 (95%CI: 6.93 ~ 7.09), and then Re declined sharply to below 1.0 on October 6, 2022. Scenario analysis of higher stringency measures showed the importance of decreasing the transmission rate and increasing the quarantine rate to shorten the time to peak, dynamic zero-COVID and an Re below 1.0, as well as to reduce the number of peak cases and final affected population.

Conclusion

Our model was effective in predicting the epidemic trends of COVID-19, and the implementation of a more stringent combination of measures was indispensable in containing the spread of the virus.

Risk factors associated with indoor transmission during home quarantine of COVID-19 patients

Purpose

The study aimed to identify potential risk factors for family transmission and to provide precautionary guidelines for the general public during novel Coronavirus disease 2019 (COVID-19) waves.

Methods

A retrospective cohort study with numerous COVID-19 patients recruited was conducted in Shanghai. Epidemiological data including transmission details, demographics, vaccination status, symptoms, comorbidities, antigen test, living environment, residential ventilation, disinfection and medical treatment of each participant were collected and risk factors for family transmission were determined.

Results

A total of 2,334 COVID-19 patients participated. Compared with non-cohabitation infected patients, cohabitated ones were younger (p = 0.019), more commonly unvaccinated (p = 0.048) or exposed to infections (p < 0.001), and had higher rates of symptoms (p = 0.003) or shared living room (p < 0.001). Risk factors analysis showed that the 2019-nCov antigen positive (OR = 1.86, 95%CI 1.40-2.48, p < 0.001), symptoms development (OR = 1.86, 95%CI 1.34-2.58, p < 0.001), direct contact exposure (OR = 1.47, 95%CI 1.09-1.96, p = 0.010) were independent risk factors for the cohabitant transmission of COVID-19, and a separate room with a separate toilet could reduce the risk of family transmission (OR = 0.62, 95%CI 0.41-0.92, p = 0.018).

Conclusion

Patients showing negative 2019-nCov antigen tests, being asymptomatic, living in a separate room with a separate toilet, or actively avoiding direct contact with cohabitants were at low risk of family transmission, and the study recommended that avoiding direct contact and residential disinfection could reduce the risk of all cohabitants within the same house being infected with COVID-19.

The Role of Vaccination and Face Mask Wearing on COVID-19 Infection and Hospitalization: A Cross-Sectional Study of the MENA Region

Since the emergence of the Coronavirus disease (COVID-19) pandemic, the disease has affected more than 675 million people worldwide, including more than 6.87 million deaths. To mitigate the effects of this pandemic, many countries established control measures to contain its spread. Their riposte was based on a combination of pharmaceutical (vaccination) and non-pharmaceutical (such as facemask wearing, social distancing, and quarantine) measures. In this way, cross-sectional research was conducted in Algeria from 23 December 2021 to 12 March 2022 to investigate the effectiveness of preventative interventions in lowering COVID-19 infection and severity. More specifically, we investigated the link between mask-wearing and infection on one side, and the relationship between vaccination and the risk of hospitalization on the other. For this purpose, we used binary logistic regression modeling that allows learning the role of mask-wearing and vaccination in a heterogeneous society with respect to compliance with barrier measures. This study determined that wearing a mask is equally important for people of all ages. Further, findings revealed that the risk of infection was 0.79 times lower among those who were using masks (odds ratio (OR) = 0.79; confidence interval (CI) 95% = 0.668-0.936; p-value = 0.006). At the same time, vaccination is a necessary preventive measure as the risk of hospitalization increases with age. Compared with those who did not get vaccinated, those who got vaccinated were 0.429 times less likely to end up in the hospital (OR = 0.429; CI95% = 0.273-0.676; p < 0.0001). The model performance demonstrates significant relationships between the dependent and independent variables, with the absence of over-dispersion in both studied models, such as the Akaike Information Criterion (AIC) scores. These findings emphasize the significance of preventative measures and immunization in the battle against the COVID-19 pandemic.

The Effect of Preventive Measures and Vaccination against SARS-CoV-2 on the Infection Risk, Treatment, and Hospitalization: A Cross-Sectional Study of Algeria

Coronavirus disease (COVID-19) caused by the SARS-CoV-2 virus continues to afflict many countries around the world. The resurgence of COVID-19 cases and deaths in many countries shows a complacency in adhering to preventive guidelines. Consequently, vaccination continues to be a crucial intervention to reduce the effects of this pandemic. This study investigated the impact of preventive measures and COVID-19 vaccination on the infection, medication, and hospitalization. A cross-sectional online survey was conducted between 23 December 2021 and 12 March 2022 in Algeria. To evaluate the effectiveness of strategies aimed at avoiding and minimizing SARS-CoV-2 infection and severity, a questionnaire was created and validated. Descriptive statistics and logistic regression analyses were computed to identify associations between dependent and independent variables. Variables with a p-value of < 0.05 were considered statistically significant. Our results indicated that out of 2294 answers received, only 16% of our sample was vaccinated, and more than 60% did not apply preventive guidelines. As a result, 45% were infected with SARS-CoV-2, 75% took treatment (even preventive), and 9% were hospitalized. The logistic regression showed that the impact of preventive measures on the unvaccinated is statistically not significant (OR: 0.764, 95% CI = 0. 555-1.052; p = 0.09). However, this relationship changes significantly for people who are vaccinated (OR: 0.108, 95% CI = 0.047-0.248; p < 0.0001). Our results also demonstrated that the impact of protective measures on non-vaccinated individuals is statistically significant in reducing the need to receive anti-COVID-19 treatments (OR: 0.447, 95% CI = 0.321-0.623; p < 0.0001). Furthermore, the results showed that the impact of preventive measures on the non-vaccinated population is also statistically significant in reducing the risk of hospitalization (OR: 0.211, 95% CI = 0.081-0.548; p < 0.0001). Moreover, vaccinated individuals who neglect preventive measures must take the COVID-19 medication at a rate of 3.77 times (OR: 3.77) higher than those who follow preventive measures and are vaccinated. In short, our findings demonstrate the importance of combining preventive measures and vaccination in order to fight against the pandemic. Therefore, we advise the Ministry of Health and relevant authorities to put more effort into enhancing public knowledge about the COVID-19 infection and vaccination through education and awareness initiatives. Parallel to implementing vaccination as additional preventive strategy, behavioral change initiatives must be improved to encourage adherence to COVID-19 prevention recommendations.

Prevalence and associated factors of COVID-19 among Moroccan physicians: A cross-sectional study

BACKGROUND

Coronavirus disease (COVID-19) has emerged and spread rapidly worldwide and established a global public health crisis in early 2020. The first Moroccan case was reported on March 2, 2020. Since then, healthcare workers (HCWs) played a major role in saving human lives threatened by COVID-19. This study aimed to assess the prevalence of COVID-19 infection among Moroccan physicians and to report associated risk factors prior vaccination campaign.

METHODS

A cross-sectional study was carried out in the Fez-Meknes region of Morocco, 545 physicians' data was collected using a self-reported online questionnaire. The data collection was done between December 1, 2020, and February 1, 2021.

RESULTS

The prevalence of COVID-19 among physicians was 27.3%. The mean age of the confirmed COVID-19 group was 38.4±12.9 years old. There was no association between COVID-19 infection and preventive measures compliance by physicians and healthcare authorities in the workplace. However, multivariate analysis strengthened the following factors such as increased risk of COVID-19 infection within men ☯aOR:1.896; 95% IC 1.272-2.828; p = 0.002]; the presence of at least one comorbidity ☯aOR:2.268; 95%IC 1.414-3.637; p = 0.001]; and working at a university or military hospitals ☯aOR:2.578; 95%IC 1.667-3.989; p = 0.001].

CONCLUSION

This study allows comparing COVID-19 prevalence among healthcare workers before and after vaccination programs. This should support better preparation strategy for any future pandemics with appropriate and increased awareness for men, carrying comorbidity, and working environment with high COVID-19 disease management.

Development of gold nanoparticle-based biosensors for COVID-19 diagnosis

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative organism of coronavirus disease 2019 (COVID-19) which poses a significant threat to public health worldwide. Though there are certain recommended drugs that can cure COVID-19, their therapeutic efficacy is limited. Therefore, the early and rapid detection without compromising the test accuracy is necessary in order to provide an appropriate treatment for the disease suppression.

Main body

Nanoparticles (NPs) can closely mimic the virus and interact strongly with its proteins due to their morphological similarities. NPs have been widely applied in a variety of medical applications, including biosensing, drug delivery, antimicrobial treatment, and imaging. Recently, NPs-based biosensors have attracted great interest for their biological activities and specific sensing properties, which allows the detection of analytes such as nucleic acids (DNA or RNA), aptamers, and proteins in clinical samples. Further, the advances of nanotechnologies have enabled the development of miniaturized detection systems for point-of-care biosensors, a new strategy for detecting human viral diseases. Among the various NPs, the specific physicochemical properties of gold NPs (AuNPs) are being widely used in the field of clinical diagnostics. As a result, several AuNP-based colorimetric detection methods have been developed.

Short conclusion

The purpose of this review is to provide an overview of the development of AuNPs-based biosensors by virtue of its powerful characteristics as a signal amplifier or enhancer that target pathogenic RNA viruses that provide a reliable and effective strategy for detecting of the existing or newly emerging SARS-CoV-2.

Bayesian Modeling of COVID-19 to Classify the Infection and Death Rates in a Specific Duration: The Case of Algerian Provinces

COVID-19 causes acute respiratory illness in humans. The direct consequence of the spread of the virus is the need to find appropriate and effective solutions to reduce its spread. Similar to other countries, the pandemic has spread in Algeria, with noticeable variation in mortality and infection rates between regions. We aimed to estimate the proportion of people who died or became infected with SARS-CoV-2 in each provinces using a Bayesian approach. The estimation parameters were determined using a binomial distribution along with an a priori distribution, and the results had a high degree of accuracy. The Bayesian model was applied during the third wave (1 January-15 August 2021), in all Algerian's provinces. For spatial analysis of duration, geographical maps were used. Our findings show that Tissemsilt, Ain Defla, Illizi, El Taref, and Ghardaia (Mean = 0.001) are the least affected provinces in terms of COVID-19 mortality. The results also indicate that Tizi Ouzou (Mean = 0.0694), Boumerdes (Mean = 0.0520), Annaba (Mean = 0.0483), Tipaza (Mean = 0.0524), and Tebessa (Mean = 0.0264) are more susceptible to infection, as they were ranked in terms of the level of corona infections among the 48 provinces of the country. Their susceptibility seems mainly due to the population density in these provinces. Additionally, it was observed that northeast Algeria, where the population is concentrated, has the highest infection rate. Factors affecting mortality due to COVID-19 do not necessarily depend on the spread of the pandemic. The proposed Bayesian model resulted in being useful for monitoring the pandemic to estimate and compare the risks between provinces. This statistical inference can provide a reasonable basis for describing future pandemics in other world geographical areas.

The Importance of Behavioral and Native Factors on COVID-19 Infection and Severity: Insights from a Preliminary Cross-Sectional Study

The COVID-19 pandemic has had a major impact on a global scale. Understanding the innate and lifestyle-related factors influencing the rate and severity of COVID-19 is important for making evidence-based recommendations. This cross-sectional study aims at establishing a potential relationship between human characteristics and vulnerability/resistance to SARS-CoV-2. We hypothesize that the impact of the virus is not the same due to cultural and ethnic differences. A cross-sectional study was performed using an online questionnaire. The methodology included the development of a multi-language survey, expert evaluation, and data analysis. Data were collected using a 13-item pre-tested questionnaire based on a literature review between 9 December 2020 and 21 July 2021. Data were statistically analyzed using logistic regression. For a total of 1125 respondents, 332 (29.5%) were COVID-19 positive; among them, 130 (11.5%) required home-based treatment, and 14 (1.2%) intensive care. The significant and most influential factors on infection included age, physical activity, and health status (p < 0.05), i.e., better physical activity and better health status significantly reduced the possibility of infection, while older age significantly increased it. The severity of infection was negatively associated with the acceptance (adherence and respect) of preventive measures and positively associated with tobacco (p < 0.05), i.e., smoking regularly significantly increases the severity of COVID-19 infection. This suggests the importance of behavioral factors compared to innate ones. Apparently, individual behavior is mainly responsible for the spread of the virus. Therefore, adopting a healthy lifestyle and scrupulously observing preventive measures, including vaccination, would greatly limit the probability of infection and prevent the development of severe COVID-19.

Characterization and Planning of Household Waste Management: A Case Study from the MENA Region

Solid waste management is one of the most important environmental issues worldwide, particularly in MENA countries. The present study was carried out in the city of Algiers, the capital city of Algeria. This urban area is marked by an increase in waste flow combined with a demographic surge. In order to investigate waste production and its drivers, we used both multiple regression and correlation analyses to test this dependence. Geospatial analysis was performed using principal component analysis integrated with GIS in order to look at the spatial distribution of waste management and potential drivers of waste production. The results indicate that household waste management is influenced by drivers related to the size of the settlement and the characteristics of waste management companies (p ≤ 0.05). The findings also show that none of the sociodemographic variables were found to significantly influence waste production. However, the spatial distribution is influenced by the geographic and sociodemographic characteristics of Algeria at all territorial levels. Algiers is still a landfill-based city in the MENA region, where mixed waste collection prevails in all districts. This study reinforces the importance of expanding source-separated waste collection schemes in order to increase the household waste diversion from landfills and, more importantly, shows how modern tools such as GIS, principal component analysis, and spatial analysis urban planning are useful for monitoring household waste, in line with circular economy principles.

Intention to get COVID-19 vaccination and its associated predictors: A cross-sectional study among the general public in Algeria

Background

Hesitancy towards COVID-19 vaccination and its rejection remains a major public health concern worldwide, especially in the Middle East and North African countries. The current study aimed to assess the intentions to get COVID-19 vaccines and its determinants among the general public in Algeria.

Methods

A self-administered online survey was distributed during August-September 2021 using a convenience-based sampling approach. Data were collected anonymously and analyzed using IBM SPSS v22.0 software.

Results

The study sample comprised a total of 656 participants, with 51.1% being in favor of COVID-19 vaccines while 18.5% and 30.5% were against or hesitant respectively. Only 38.6% among the study participants got vaccinated. Factors associated with higher odds of acceptance were: male sex, healthcare profession, the belief in natural origin of the pandemic and previous COVID-19 infection in family. The most common cited reasons for COVID-19 vaccine acceptance were the belief that vaccination is the only way to fight COVID-19 and the fear of getting infected by the virus; while the most common reasons of rejection were lack of trust in proper vaccine testing and fear of side effects.

Conclusion

The overall level of COVID-19 vaccine acceptance in this study was below the levels required to achieve population immunity. Besides certain socio-demographic characteristics, the determinants of COVID-19 vaccine rejection included the embrace of conspiratorial ideas regarding the virus and its vaccination. This should be considered in implementation of interventional measures aiming to promote COVID-19 vaccination in the country.