Background During the COVID-19 pandemic, Santé publique France (SpF) published incidence (SpFi) rates based on census denominators. Denominators using cell phone connection (CPC) data can better reflect the population present and seasonal mobilities. Aim Given uncertainties regarding the actual number of Île-de-France (IdF) residents present in IdF during summer 2021, we aimed to better approximate true incidence rates from positive SARS-CoV-2 tests in IdF using CPC-derived population denominators. Method This longitudinal study used the daily number of positive tests (PCR and Ag) on IdF residents in IdF as the numerator and the estimated resident population present in IdF at midnight as the denominator. We computed the mean corrected incidence rate (MCIR) per moving week between 4 July and 9 September 2021. Results The MCIR showed higher incidence rates than initially estimated, especially during August when residents had left IdF for the holidays. Incidence rates reached a peak on 16 August when the SpFi rate per moving week was 200.9 per 100,000 compared with 315.6 per 100,000 with the MCIR, representing a 57% increase. Conclusion Using local SARS-CoV-2 testing data and real-time population denominators, we showed that indicators using non-geographically referenced test results and fixed population denominators that ignore seasonal mobility can significantly underestimate incidence rates in IdF. New data sources using CPC data provide the opportunity to calculate more accurate and dynamic incidence rates and to map epidemics more precisely and in real time.

Yearly bronchiolitis and influenza-like illness epidemics in France often involve high morbidity and mortality, which severely impact health care. Epidemics are declared by the French National Institute of Public Health based on syndromic surveillance of primary care and emergency departments (EDs), using statistics-based alarms. Although the effective reproduction number (Rt) is used to monitor the dynamics of epidemics, it has never been used as an early-warning tool for bronchiolitis or influenza-like illness epidemics in France. We assessed whether Rt is useful for detecting seasonal epidemics by comparing it to the tool currently used (MASS) by epidemiologists to declare epidemic phases. We used anonymized ED syndromic data from the Île-de-France region in France from 2010 to 2022. We estimated Rt and compared the indication of accelerated transmission (Rt > 1) to the MASS epidemic alarm time points. We computed the difference between those 2 time points, time to epidemic peak, and the daily cases documented at first indication and peak. Rt provided alarms for influenza-like illness and bronchiolitis epidemics that were, respectively, a median of 6 days (IQR, 4, 8) and 64 days (IQR, 52, 80) earlier than the alarms provided by MASS. Rt detected earlier signals of bronchiolitis and influenza-like illness epidemics. Using this early-warning indicator in combination with others to declare an annual epidemic could provide opportunities to improve health care system readiness.

Sheep primary epithelial cells are short-lived in cell culture systems. For long-term in vitro studies, primary cells need to be immortalized. This study aims to establish and characterize T immortalized sheep embryo kidney cells (TISEKC). In this study, we used fetal lamb kidneys to derive primary cultures of epithelial cells. We subsequently immortalized these cells using the large T SV40 antigen to generate crude TISEKC and isolate TISEKC clones. Among numerous clones of immortalized cells, the selected TISEKC-5 maintained active division and cell growth over 20 passages but lacked expression of the oncogenic large T SV40 antigen. Morphologically, TISEKC-5 maintained their epithelial aspect similar to the parental primary epithelial cells. However, their growth properties showed quite different patterns. Crude TISEKC, as well as the clones of TISEKC proliferated highly in culture compared to the parental primary cells. In the early passages, immortalized cells showed heterogeneous polyploidy but in the late passages the karyotype of immortalized cells became progressively stable, identical to that of the primary cells, because the TISEKC-5 cell line has lost the large SV40 T antigen expression, this cell line is a valuable tool for veterinary sciences and biotechnological productions.

OBJECTIVES:Natural disasters (NDs) may increase the outbreaks and transmissions of vector-borne diseases such as cutaneous leishmaniasis (CL) and visceral leishmaniasis (VL). However, the relationship between leishmaniases and NDs has not yet been clearly established. Here, we systematically reviewed all reported articles in this field to answer whether NDs increase the frequency of leishmaniases.METHODS:All the related articles published during January 2000 till January 2020 were reviewed. Moreover, all NDs and the associated leishmaniases frequencies reports in 17 leishmaniases endemic countries were searched to find any ND-leishmaniases relationship.RESULTS:After the initial screening, 39 articles on ND-leishmaniases were selected and systematically reviewed. These articles showed different frequencies of CL in the endemic areas before and after NDs in some regions of Pakistan and Iran and in case of VL in Brazil, Ethiopia, and Sudan. After thorough deliberation, four studies for CL-ND and five studies for VL-ND relationships were selected for meta-analysis. The results showed increases in the leishmaniases incidences after NDs, although not robustly.CONCLUSION:The lack of a strong leishmaniases-ND relationship could be attributed to the local compilations of such data in scattered regions of the endemic countries. Therefore, currently a substantial knowledge gap on leishmaniases-ND relationship is apparent.

Estimate of the ABSTRACT Since December 2019, the world has been incrementally invaded by SARS-CoV-2. Algeria is affected since February 25, 2020. In order to benefit from its experience, this study aims to describe the epidemic ’ s current situation and then retrospectively estimate its real burden. First, we described the epidemic ’ s indicators as; cases, deaths, and we computed the R0 evolution. Secondly, we used the New York City cases-fatality rate standardized by Algerian age structure, to retrospectively estimate the actual burden. The reported cases are in a clear diminution, but, the epidemic epicentre is moving from Blida to other cities. We noted a clear peak in daily cases-fatality from March 30, to April 17, 2020, due to underestimating the actual infections of the first 25 days. Since May 8, 2020, the daily R0 is around one. Moreover, we noticed 31% reduction of its mean value from 1,41 to 0,97 between the last two months. The Algerian Age-Standardized Infection Fatality Rate we found is 0,88%. Based on that, we demonstrated that only 1,5% of actual infections were detected and reported before March 30, and 20% after March 31. Therefore, the actual infections burden is currently five times higher than reported. At the end, we found that at least 0,2 % of the population have been infected until May 27. The under estimation of the epidemic ’ s actual burden is probably due to the lack of testing capacities, however, all the indicators show that the situation is currently controlled.

Introduction: Since December 29, 2019 a pandemic of new novel coronavirus-infected pneumonia named COVID-19 has started from Wuhan, China, has led to 254 996 confirmed cases until midday March 20, 2020. Sporadic cases have been imported worldwide, in Algeria, the first case reported on February 25, 2020 was imported from Italy, and then the epidemic has spread to other parts of the country very quickly with 139 confirmed cases until March 21, 2020. Methods: It is crucial to estimate the cases number growth in the early stages of the outbreak, to this end, we have implemented the Alg-COVID-19 Model which allows to predict the incidence and the reproduction number R0 in the coming months in order to help decision makers. The Alg-COVIS-19 Model initial equation 1, estimates the cumulative cases at t prediction time using two parameters: the reproduction number R0 and the serial interval SI. Results: We found R0=2.55 based on actual incidence at the first 25 days, using the serial interval SI= 4,4 and the prediction time t=26. The herd immunity HI estimated is HI=61%. Also, The Covid-19 incidence predicted with the Alg-COVID-19 Model fits closely the actual incidence during the first 26 days of the epidemic in Algeria Fig. 1.A. which allows us to use it.

Since December 2019, the five continents have been incrementally invaded by SARS-CoV-2. Africa is the last and least affected to date. However, Algeria is among the first countries affected since February 25, 2020. In order to benefit from its experience in the least affected countries, this study aims to describe the current situation of the epidemic and then retrospectively estimate its real burden. As a first part of the study, we described the indicators of the epidemic as; the cumulative and daily reported cases and deaths, and we computed the R0 evolution. Secondly, we used the New York City cases-fatality rate standardized by Algerian age structure, to retrospectively estimate the actual burden. We found that reported cases are in a clear diminution, but, the epidemic epicentre is moving from Blida to other cities. We noted a clear peak in daily cases-fatality from March 30, to April 17, 2020, Fig. 3, due to underestimating the actual infections of the first 25 days. Since May 8, 2020, the daily R0 is around one, Fig. 4. Moreover, we noticed 31% reduction of its mean value from 1,41 to 0,97 between the last two months. The Algerian Age-Standardized Infection Fatality Rate we found is 0,88%. Based on that, we demonstrated that only 1,5% of actual infections were detected and reported before March 30, and 20% after March 31, Fig. 5. Therefore, the actual infections burden is currently five times higher than reported. At the end, we found that at least 0,2 % of the population have been infected until May 27. Consequently, the acquired herd immunity to date is therefore not sufficient to avoid a second wave. We believe that, the under estimation of the actual burden of the epidemic is probably due to the lack of testing capacities, however, all the indicators show that the situation is currently controlled. This requires more vigilance for the next weeks during the gradual easing of the preventive measures.

AbstractIntroductionSince December 29, 2019 a pandemic of new novel coronavirus-infected pneumonia named COVID-19 has started from Wuhan, China, has led to 254 996 confirmed cases until midday March 20, 2020. Sporadic cases have been imported worldwide, in Algeria, the first case reported on February 25, 2020 was imported from Italy, and then the epidemic has spread to other parts of the country very quickly with 139 confirmed cases until March 21, 2020.MethodsIt is crucial to estimate the cases number growth in the early stages of the outbreak, to this end, we have implemented the Alg-COVID-19 Model which allows to predict the incidence and the reproduction number R0 in the coming months in order to help decision makers.The Alg-COVIS-19 Model initial equation 1, estimates the cumulative cases at t prediction time using two parameters: the reproduction number R0 and the serial interval SI.ResultsWe found R0=2.55 based on actual incidence at the first 25 days, using the serial interval SI= 4,4 and the prediction time t=26. The herd immunity HI estimated is HI=61%. Also, The Covid-19 incidence predicted with the Alg-COVID-19 Model fits closely the actual incidence during the first 26 days of the epidemic in Algeria Fig. 1.A. which allows us to use it.According to Alg-COVID-19 Model, the number of cases will exceed 5000 on the 42th day (April 7th) and it will double to 10000 on 46th day of the epidemic (April 11th), thus, exponential phase will begin (Table 1; Fig.1.B) and increases continuously until reaching à herd immunity of 61% unless serious preventive measures are considered.DiscussionThis model is valid only when the majority of the population is vulnerable to COVID-19 infection, however, it can be updated to fit the new parameters values.

Virus neutralisation test (VNT) of capripoxvirus (CaPVs) was studied to assess the post-vaccination (vaccine effectiveness) or post-infection antibodies level using two methods: alpha-VNT and beta-VNT which are generally carried out to measure the Neutralising Index (N.I.) and the serum Antibody titre (TAb) respectively. The authors have demonstrated that a positive correlation exists between N.I. and TAb values, this study aimed to add more evidence to this correlation by establishing a graph and its mathematical equations. We found that: N.I. = (1.489 Log TAb) + 1.331; this serves as a base to calculate N.I. using TAb values measured by beta-VNT without going through alpha-VNT and vice versa. At the end of this study, we evaluated the equation accuracy by two parameters; the deviation (d) and the error percentage, which were d = 0.2 and error (%) = 8%, respectively.