Dataset Information

Epidemiological Patterns of Seasonal Respiratory Viruses during the COVID-19 Pandemic in Madagascar, March 2020-May 2022.

ABSTRACT: Three epidemic waves of coronavirus disease-19 (COVID-19) occurred in Madagascar from March 2020 to May 2022, with a positivity rate of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) of 21% to 33%. Our study aimed to identify the impact of COVID-19 on the epidemiology of seasonal respiratory viruses (RVs) in Madagascar. We used two different specimen sources (SpS). First, 2987 nasopharyngeal (NP) specimens were randomly selected from symptomatic patients between March 2020 and May 2022 who tested negative for SARS-CoV-2 and were tested for 14 RVs by multiplex real-time PCR. Second, 6297 NP specimens were collected between March 2020 and May 2022 from patients visiting our sentinel sites of the influenza sentinel network. The samples were tested for influenza, respiratory syncytial virus (RSV), and SARS-CoV-2. From SpS-1, 19% (569/2987) of samples tested positive for at least one RV. Rhinovirus (6.3%, 187/2987) was the most frequently detected virus during the first two waves, whereas influenza predominated during the third. From SpS-2, influenza, SARS-CoV-2, and RSV accounted for 5.4%, 24.5%, and 39.4% of the detected viruses, respectively. During the study period, we observed three different RV circulation profiles. Certain viruses circulated sporadically, with increased activity in between waves of SARS-CoV-2. Other viruses continued to circulate regardless of the COVID-19 situation. Certain viruses were severely disrupted by the spread of SARS-CoV-2. Our findings underline the importance and necessity of maintaining an integrated disease surveillance system for the surveillance and monitoring of RVs of public health interest.

SUBMITTER: Razanajatovo NH

PROVIDER: S-EPMC9864023 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Epidemiological Patterns of Seasonal Respiratory Viruses during the COVID-19 Pandemic in Madagascar, March 2020-May 2022.

Razanajatovo Norosoa Harline NH Randriambolamanantsoa Tsiry Hasina TH Rabarison Joelinotahiana Hasina JH Randrianasolo Laurence L Ankasitrahana Miamina Fidy MF Ratsimbazafy Arvé A Raherinandrasana Antso Hasina AH Razafimanjato Helisoa H Raharinosy Vololoniaina V Andriamandimby Soa Fy SF Heraud Jean-Michel JM Dussart Philippe P Lacoste Vincent V

Viruses 20221220 1

Three epidemic waves of coronavirus disease-19 (COVID-19) occurred in Madagascar from March 2020 to May 2022, with a positivity rate of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) of 21% to 33%. Our study aimed to identify the impact of COVID-19 on the epidemiology of seasonal respiratory viruses (RVs) in Madagascar. We used two different specimen sources (SpS). First, 2987 nasopharyngeal (NP) specimens were randomly selected from symptomatic patients between March 2020 and May ...[more]

PMID: 36680053

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Project description:AimsMitigation actions during the COVID-19 pandemic may impact mental health and suicide in general populations. We aimed to analyse the evolution in suicide deaths from 2020 to March 2022 in France.MethodsUsing free-text medical causes in death certificates, we built an algorithm, which aimed to identify suicide deaths. We measured its retrospective performances by comparing suicide deaths identified using the algorithm with deaths which had either a Tenth revision of the International Classification of Diseases (ICD-10) code for 'intentional self-harm' or for 'external cause of undetermined intent' as the underlying cause. The number of suicide deaths from January 2020 to March 2022 was then compared with the expected number estimated using a generalized additive model. The difference and the ratio between the observed and expected number of suicide deaths were calculated on the three lockdown periods and for periods between lockdowns and after the third one. The analysis was stratified by age group and gender.ResultsThe free-text algorithm demonstrated high performances. From January 2020 to mid-2021, suicide mortality declined during France's three lockdowns, particularly in men. During the periods between and after the two first lockdowns, suicide mortality remained comparable to the expected values, except for men over 85 years old and in 65-84 year-old age group, where a small number of excess deaths was observed in the weeks following the end of first lockdown, and for men aged 45-64 years old, where the decline continued after the second lockdown ended. After the third lockdown until March 2022, an increase in suicide mortality was observed in 18-24 year-old age group for both genders and in men aged 65-84 years old, while a decrease was observed in the 25-44 year-old age group.ConclusionsThis study highlighted the absence of an increase in suicide mortality during France's COVID-19 pandemic and a substantial decline during lockdown periods, something already observed in other countries. The increase in suicide mortality observed in 18-24 year-old age group and in men aged 65-84 years old from mid-2021 to March 2022 suggests a prolonged impact of COVID-19 on mental health, also described on self-harm hospitalizations and emergency department's attendances in France. Further studies are required to explain the factors for this change. Reactive monitoring of suicide mortality needs to be continued since mental health consequences and the increase in suicide mortality may be continued in the future with the international context.

Project description:Infectious serositis is a common disease caused by Riemerella anatipestifer (R. anatipestifer) in ducks, characterized by respiratory distress, septicemia, and neurological symptoms. In this study, 1,020 samples (brain and liver) were collected from ducks with suspected R. anatipestifer infection from March 2020 to March 2022 in Shandong Province, of which 171 R. anatipestifer strains were identified by PCR and isolation culture. The serotype of all strains was analyzed, and 74 strains were subjected to drug sensitivity tests and drug resistance genes detection. The results showed that the overall prevalence rate of R. anatipestifer in Shandong Province was 16.7% (171/1,020), with most strains coming from brain samples of ducklings under 3-mo old collected from September to December each year. Histopathological examination showed that heart vessels of the diseased duck were highly dilated and filled with red blood cells, with obvious fibrin exudates outside the pericardium, and fatty degeneration of liver cells. There were 45 strains of serotype 1, 45 strains of serotype 2, 2 strains of serotype 4, 33 strains of serotype 6, 44 strains of serotype 7, and 2 strains of serotype 10. The minimum inhibitory concentration (MIC) of 10 common antibiotics against 74 representative strains was determined by the agar dilution method. It was found that 74 strains had the most severe resistance to gentamicin (77%) and fully susceptible to ceftriaxone, but the 81.1% isolated strains were multidrug resistant. Resistance genes testing of 74 R. anatipestifers showed that tetracycline resistance gene tet X had the highest detection rate of 95.9%, followed by macrolide resistance gene ermF with 77%, and the rate of β-lactam resistance gene blaTEM is the lowest (10.8%). The animal experiment of 4 R. anatipestifer strains with different serotypes showed that they had strong pathogenicity to 7-day-old ducklings, which could cause nervous symptoms, and the mortality rate was 58% to 70%. The autopsy showed obvious pathological changes. These findings of this study on R. anatipestifer will help us to understand the latest prevalence, drug resistance characteristics, and pathogenicity of R. anatipestifer in Shandong, China, and provide a scientific guide for the treatment and control of the disease.

Project description:ImportanceThe reported incidence of many health care-associated infections (HAIs) increased during the COVID-19 pandemic; however, it is unclear whether this is due to increased patient risk or to increased pressure on the health care system.ObjectiveTo assess HAI occurrence among patients admitted to hospitals with and without COVID-19.Design, setting, and participantsA cross-sectional retrospective analysis of inpatients discharged both with and without laboratory-confirmed COVID-19 infection was conducted. Data were obtained between January 1, 2019, and March 31, 2022, from community hospitals affiliated with a large health care system in the US.ExposureCOVID-19 infection.Main outcomes and measuresOccurrence of central line-associated bloodstream infection (CLABSI), catheter-associated urinary tract infection (CAUTI), methicillin-resistant Staphylococcus aureus (MRSA) bacteremia, and Clostridioides difficile infection as reported to the National Healthcare Safety Network.ResultsAmong nearly 5 million hospitalizations in 182 hospitals between 2020 and 2022, the occurrence of health care-associated infections (HAIs) was high among the 313 200 COVID-19 inpatients (median [SD] age, 57 [27.3] years; 56.0% women). Incidence per 100 000 patient-days showed higher HAIs among those with COVID-19 compared with those without. For CLABSI, the incidence for the full 9 quarters of the study was nearly 4-fold higher among the COVID-19 population than the non-COVID-19 population (25.4 vs 6.9). For CAUTI, the incidence in the COVID-19 population was 2.7-fold higher in the COVID-19 population (16.5 vs 6.1), and for MRSA, 3.0-fold higher (11.2 vs 3.7). Quarterly trends were compared with the same quarter in 2019. The greatest increase in the incidence of HAI in comparison with the same quarter in 2019 for the entire population occurred in quarter 3 of 2020 for CLABSI (11.0 vs 7.3), quarter 4 of 2021 for CAUTI (7.8 vs 6.8), and quarter 3 of 2021 for MRSA (5.2 vs 3.9). When limited to the non-COVID-19 population, the increase in CLABSI incidence vs the 2019 incidence was eliminated, and the quarterly rates of MRSA and CAUTI were lower vs the prepandemic 2019 comparator quarter.Conclusions and relevanceIn this cross-sectional study of hospitals during the pandemic, HAI occurrence among inpatients without COVID-19 was similar to that during 2019 despite additional pressures for infection control and health care professionals. The findings suggest that patients with COVID-19 may be more susceptible to HAIs and may require additional prevention measures.

Project description:During the SARS-CoV-2 pandemic, governments and public health authorities collected massive amounts of data on daily confirmed positive cases and incidence rates. These data sets provide relevant information to develop a scientific understanding of the pandemic's spatiotemporal dynamics. At the same time, there is a lack of comprehensive approaches to describe and classify patterns underlying the dynamics of COVID-19 incidence across regions over time. This seriously constrains the potential benefits for public health authorities to understand spatiotemporal patterns of disease incidence that would allow for better risk communication strategies and improved assessment of mitigation policies efficacy. Within this context, we propose an exploratory statistical tool that combines functional data analysis with unsupervised learning algorithms to extract meaningful information about the main spatiotemporal patterns underlying COVID-19 incidence on mainland Portugal. We focus on the timeframe spanning from August 2020 to March 2022, considering data at the municipality level. First, we describe the temporal evolution of confirmed daily COVID-19 cases by municipality as a function of time, and outline the main temporal patterns of variability using a functional principal component analysis. Then, municipalities are classified according to their spatiotemporal similarities through hierarchical clustering adapted to spatially correlated functional data. Our findings reveal disparities in disease dynamics between northern and coastal municipalities versus those in the southern and hinterland. We also distinguish effects occurring during the 2020-2021 period from those in the 2021-2022 autumn-winter seasons. The results provide proof-of-concept that the proposed approach can be used to detect the main spatiotemporal patterns of disease incidence. The novel approach expands and enhances existing exploratory tools for spatiotemporal analysis of public health data.

Dataset Information

Epidemiological Patterns of Seasonal Respiratory Viruses during the COVID-19 Pandemic in Madagascar, March 2020-May 2022.

Publications

Epidemiological Patterns of Seasonal Respiratory Viruses during the COVID-19 Pandemic in Madagascar, March 2020-May 2022.

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