Background:Since 2020, global attention has heightened towards epidemics caused by avian influenza A H5N1 virus of clade 2.3.4.4b in birds and mammals. This study presents the epidemiological history, clinical manifestations, and prognosis of a unique case infected with avian influenza A H5N1 clade 2.3.4.4b, along with the continuation of SARS-CoV-2 viral RNAs, in Eastern China. Methods:We collected and analysed the patient's clinical, epidemiological, and virological data. Both sputum and bronchoalveolar lavage fluid (BALF) samples were subjected to real-time RT-PCR to test for respiratory pathogens of interests, including SARS-CoV-2 and influenza virus. Influenza virus isolation and propagation were performed on embryonated eggs. Serological tests were used to determine the presence of SARS-CoV-2 antibodies. Phylogenetic analysis was constructed to explore viral evolution and origin of A/H5N1 virus. Results:A 53-year-old female farmer with chronic bronchiectasis was hospitalized with severe pneumonia. Real-time RT-PCR revealed the presence of avian influenza A H5N1 and SARS-CoV-2 in BALF and sputum samples. Sequence analyses classified the human isolate as clade 2.3.4.4b of avian influenza A H5N1. The amino acid motif GlnSerGly at residues 226-228 of the haemagglutinin protein indicated avian-like receptor binding preference. Epidemiological investigation established that the patient had exposure to sick or dead poultry 3 days before illness onset, while no cases of human-to-human H5N1 virus transmission were identified in 31 close contacts. Conclusion:We presented that the clade 2.3.4.4b H5N1 avian influenza virus has the potential to cross-infect humans with serious symptoms, especially in individuals already affected by COVID-19. It is indeed crucial to closely monitor the virus's evolution in both avian populations and humans. Continued research and surveillance efforts are vital to monitor any potential changes in the virus, as well as to inform public health policies and interventions.

BackgroundSARS-CoV-2 strains have been of great concern due to their high infectivity and antibody evasion.MethodsIn this study, data were collected on indigenous aggregated outbreaks in Nanjing from January 2020 to December 2022, caused by five strains including the original strain, the Delta variant, and the Omicron variant (BA.2, BA.5.2, and BF.7). The basic epidemiological characteristics of infected individuals were described and then parametric analysis of transmission dynamics was performed, including the calculation of incubation period, serial interval (SI), the basic reproductive number (R0), and the household secondary attack rate (HSAR). Finally, we compared the trends of transmission dynamic parameters of different strains.ResultsThe incubation period for the original strain, the Delta variant, Omicron BA.2, Omicron BA.5.2, and Omicron BF.7 were 6 d (95% CI: 3.5–7.5 d), 5 d (95% CI: 4.0–6.0 d), 3 d (95% CI: 3.0–4.0 d), 3 d (95% CI: 3.0–3.0 d), and 2 d (95% CI: 2.0–3.0 d), respectively; Also, the SI of the five strains were 5.69 d, 4.79 d, 2.7 d, 2.12 d, and 2.43 d, respectively. Notably, the incubation period and SI of the five had both a progressive shortening trend (p < 0.001); Moreover, R0 of the five were 2.39 (95% CI: 1.30–4.29), 3.73 (95% CI: 2.66–5.15), 5.28 (95% CI: 3.52–8.10), 5.54 (95% CI: 2.69–11.17), 7.39 (95% CI: 2.97–18.76), with an increasing trend gradually (p < 0.01); HSAR of the five were 25.5% (95% CI: 20.1–31.7%), 27.4% (95% CI: 22.0–33.4%), 42.9% (95% CI: 34.3–51.8%), 53.1% (95% CI: 45.0–60.9%), 41.4% (95% CI, 25.5–59.3%), also with an increasing trend (p < 0.001).ConclusionCompared to the original strain, the incubation period and SI decreased while R0 and HSAR increased, suggesting that transmission in the population was faster and the scope of the population was wider. Overall, it’s crucial to keep implementing comprehensive measures like monitoring and alert systems, herd immunization plans, and outbreak control.

Many studies have shown that the relationship between ambient temperature, relative humidity and mumps has been highlighted. However, these studies showed inconsistent results. Therefore, the goal of our study is to conduct a meta-analysis to clarify this relationship and to quantify the size of these effects as well as the potential factors. Systematic literature researches on PubMed, Embase.com, Web of Science Core Collection, Cochrane library, Chinese BioMedical Literature Database (CBM) and China National Knowledge Infrastructure (CNKI) were performed up to February 7, 2022 for articles analyzing the relationships between ambient temperature, relative humidity and incidence of mumps. Eligibility assessment and data extraction were conducted independently by two researchers, and meta-analysis was performed to synthesize these data. We also assessed sources of heterogeneity by study region, regional climate, study population. Finally, a total of 14 studies were screened out from 1154 records and identified to estimate the relationship between ambient temperature, relative humidity and incidence of mumps. It was found that per 1 °C increase and decrease in the ambient temperature were significantly associated with increased incidence of mumps with RR of 1.0191 (95% CI: 1.0129–1.0252, I 2 = 92.0%, Egger’s test P = 0.001, N = 13) for per 1 °C increase and 1.0244 (95% CI: 1.0130–1.0359, I 2 = 86.6%, Egger’s test P = 0.077, N = 9) for per 1 °C decrease. As to relative humidity, only high effect of relative humidity was slightly significant (for per 1 unit increase with RR of 1.0088 (95% CI: 1.0027–1.0150), I 2 = 72.6%, Egger’s test P = 0.159, N = 9). Subgroup analysis showed that regional climate with temperate areas may have a higher risk of incidence of mumps than areas with subtropical climate in cold effect of ambient temperature and low effect of relative humidity. In addition, meta-regression analysis showed that regional climate may affect the association between incidence of mumps and cold effect of ambient temperature. Our results suggest ambient temperature could affect the incidence of mumps significantly, of which both hot and cold effect of ambient temperature may increase the incidence of mumps. Further studies are still needed to clarify the relationship between the incidence of mumps and ambient temperature outside of east Asia, and many other meteorological factors. These results of ambient temperature are important for establishing preventive measures on mumps, especially in temperate areas. The policy-makers should pay more attention to ambient temperature changes and take protective measures in advance.

To understand the characteristics and influencing factors related to cluster infections in Jiangsu Province, China, we investigated case reports to explore transmission dynamics and influencing factors of scales of cluster infection. The effectiveness of interventions was assessed by changes in the time-dependent reproductive number (Rt). From 25th January to 29th February, Jiangsu Province reported a total of 134 clusters involving 617 cases. Household clusters accounted for 79.85% of the total. The time interval from onset to report of index cases was 8 days, which was longer than that of secondary cases (4 days) (χ2 = 22.763, P < 0.001) and had a relationship with the number of secondary cases (the correlation coefficient (r) = 0.193, P = 0.040). The average interval from onset to report was different between family cluster cases (4 days) and community cluster cases (7 days) (χ2 = 28.072, P < 0.001). The average time interval from onset to isolation of patients with secondary infection (5 days) was longer than that of patients without secondary infection (3 days) (F = 9.761, P = 0.002). Asymptomatic patients and non-familial clusters had impacts on the size of the clusters. The average reduction in the Rt value in family clusters (26.00%, 0.26 ± 0.22) was lower than that in other clusters (37.00%, 0.37 ± 0.26) (F = 4.400, P = 0.039). Early detection of asymptomatic patients and early reports of non-family clusters can effectively weaken cluster infections.