Control charts help epidemiologists and healthcare professionals monitor disease incidence and prevalence in real time, preventing outbreaks and health emergencies. However, there remains a notable gap in the comprehensive exploration and application of these techniques, particularly in the context of monitoring and managing disease outbreaks. This study analyses and categorizes worldwide control chart applications from 2000 to 2023 in outbreak monitoring in over 20 countries, focusing on corona-virus (COVID-19), and chooses optimal control charts for monitoring US COVID-19 death waves from February 2020 to December 2023. The systematic literature review analyzes available 35 articles, categorizing data by year, variable, country, study type, and chart design. A selected optimal chart is applied to monitor COVID-19 death patterns and waves in the USA. Control chart adoption in epidemiology monitoring increased during the COVID-19 pandemic, with annual patterns showing a rise in 2021 to 2023 (18%, 36%, 41%). Important variables from 2000 to 2019 include influenza counts, Salmonella cases, and infection rates, while COVID-19 studies focus more on cases, infection rates, symptoms, and deaths. Among 22 countries, the USA (29%) is the top applier of control charts. The monitoring of USA COVID-19 deaths reveals 8 waves with varying severity  >  >  >  >  >  >  > . The associated with the JN.1 variant, highlights ongoing challenges. This study emphasizes the significance of control charts in outbreak monitoring for early disease diagnosis and intervention. Control charts help healthcare workers manage epidemics using data-driven methods, improving public health. COVID-19 mortality analysis emphasizes their importance, encouraging worldwide use.

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BACKGROUND: Currently, different guidelines recommend using different methods to determine whether deduplication is necessary when determining the detection rates of multidrug-resistant organisms (MDROs). However, few studies have investigated the effect of deduplication on MDRO monitoring data. In this study, we aimed to investigate the influence of deduplication on the detection rates of MDROs in different specimens to assess its impact on infection surveillance outcomes.
METHODS: Samples were collected from hospitalized patients admitted between January 2022 and December 2022; four types of specimens were collected from key monitored MDROs, including sputum samples, urine samples, blood samples, and bronchoalveolar lavage fluid (BALF) samples. In this study, we compared and analysed the detection rates of carbapenem-resistant Klebsiella pneumoniae (CRKP), carbapenem-resistant Escherichia coli (CRECO), carbapenem-resistant Acinetobacter baumannii (CRAB), carbapenem-resistant Pseudomonas aeruginosa (CRPA), and methicillin-resistant Staphylococcus aureus (MRSA) under two conditions: with and without deduplication.
RESULTS: When all specimens were included, the detection rates of CRKP, CRAB, CRPA, and MRSA without deduplication (33.52%, 77.24%, 44.56%, and 56.58%, respectively) were significantly greater than those with deduplication (24.78%, 66.25%, 36.24%, and 50.83%, respectively) (all P < 0.05). The detection rates in sputum samples were significantly different between samples without duplication (28.39%, 76.19%, 46.95%, and 70.43%) and those with deduplication (19.99%, 63.00%, 38.05%, and 64.50%) (all P < 0.05). When deduplication was not performed, the rate of detection of CRKP in urine samples reached 30.05%, surpassing the rate observed with deduplication (21.56%) (P < 0.05). In BALF specimens, the detection rates of CRKP and CRPA without deduplication (39.78% and 53.23%, respectively) were greater than those with deduplication (31.62% and 42.20%, respectively) (P < 0.05). In blood samples, deduplication did not have a significant impact on the detection rates of MDROs.
CONCLUSIONS: Deduplication had a significant effect on the detection rates of MDROs in sputum, urine, and BALF samples. Based on these data, we call for the Infection Prevention and Control Organization to align its analysis rules with those of the Bacterial Resistance Surveillance Organization when monitoring MDRO detection rates.

OBJECTIVE: The recent emergence of carbapenem-resistant Enterobacterales poses a major and escalating threat to global public health. This study aimed to analyse the global distribution and antimicrobial resistance of Enterobacterales harbouring variant OXA-48-like carbapenemase-related genes.
METHODS: Enterobacterales isolates were collected from the Antimicrobial Testing Leadership and Surveillance (ATLAS) programme during 2018-2021. Comprehensive antimicrobial susceptibility testing and β-lactamase gene detection were also conducted, along with statistical analysis of the collected data.
RESULTS: Among the 72 244 isolates, 1934 Enterobacterales isolates were identified to harbour blaOXA-48-like genes, predominantly Klebsiella spp. (86.9%). High rates of multidrug resistance were observed, with only ceftazidime/avibactam and tigecycline showing favourable susceptibility. A discrepancy between the genotype and phenotype of carbapenem resistance was evident: 16.8% (233 out of 1384) of the Enterobacterales isolates with blaOXA-48-like genes exhibited susceptibility to meropenem. Specifically, 37.4% (64/95) of Escherichia coli strains with blaOXA-48-like genes displayed meropenem susceptibility, while the corresponding percentages for Klebsiella pneumoniae and Enterobacter cloacae complex were 25.2% (160/1184) and 0% (0/36), respectively (P < 0.05). Geographical analysis revealed that the highest prevalence of blaOXA-48-like genes occurred in Asia, the Middle East and Eastern Europe. The proportion of K. pneumoniae isolates harbouring blaOXA-232 increased from 23.9% in 2018 to 56.0% in 2021. By contrast, the proportion of blaOXA-48 decreased among K. pneumoniae isolates during 2018-2021.
CONCLUSIONS: This study underscores the widespread and increasing prevalence of blaOXA-48-like genes in Enterobacterales and emphasizes the need for enhanced surveillance, improved diagnostic methods and tailored antibiotic stewardship to combat the spread of these resistant pathogens.

BACKGROUND: Invasive fungal infections pose a substantial threat to patients in healthcare settings globally. Recent changes in the prevalence of fungal species and challenges in conducting reference antifungal susceptibility testing emphasize the importance of monitoring fungi and their antifungal resistance.
METHODS: A two-phase surveillance project was conducted in Beijing, China, involving 37 centres across 12 districts, from January 2012 to December 2013 and from January 2016 to December 2017.
RESULTS: We found that the proportion of Candida albicans in intensive care units (ICUs) during 2016-2017 exhibited a significant decline compared with the 2012-2013 period, although it remained the most predominant pathogen. In contrast, the prevalence of Nakaseomyces glabratus (formerly Candida glabrata) and Candida tropicalis notably increased during the two-phase surveillance. The high prevalence of C. tropicalis and its resistance to azole drugs posed a serious threat to patients in ICUs. The pathogens causing invasive fungal infections in Beijing were relatively sensitive to echinocandins. While C. albicans continued to exhibit susceptibility to azoles, the resistance and growth rates of C. tropicalis towards azoles were particularly prominent. Concerns were raised due to the emergence of multiple, short-term isolates of Clavispora lusitaniae and Candida parapsilosis complex in neonatal ICUs, given their similarity in antifungal susceptibilities. Such occurrences point towards the potential for transmission and persisting presence of these pathogens within the ICU environment.
CONCLUSIONS: Our study complements existing data on the epidemiology of invasive fungal infections. It is imperative to exercise cautious medication management for ICU patients in Beijing, paying particular attention to azole resistance in C. tropicalis.

BACKGROUND: The prevalence of different types/subtypes varies across seasons and countries for seasonal influenza viruses, indicating underlying interactions between types/subtypes. The global interaction patterns and determinants for seasonal influenza types/subtypes need to be explored.
METHODS: Influenza epidemiological surveillance data, as well as multidimensional data that include population-related, environment-related, and virus-related factors from 55 countries worldwide were used to explore type/subtype interactions based on Spearman correlation coefficient. The machine learning method Extreme Gradient Boosting (XGBoost) and interpretable framework SHapley Additive exPlanation (SHAP) were utilized to quantify contributing factors and their effects on interactions among influenza types/subtypes. Additionally, causal relationships between types/subtypes were also explored based on Convergent Cross-mapping (CCM).
RESULTS: A consistent globally negative correlation exists between influenza A/H3N2 and A/H1N1. Meanwhile, interactions between influenza A (A/H3N2, A/H1N1) and B show significant differences across countries, primarily influenced by population-related factors. Influenza A has a stronger driving force than influenza B, and A/H3N2 has a stronger driving force than A/H1N1.
CONCLUSIONS: The research elucidated the globally complex and heterogeneous interaction patterns among influenza type/subtypes, identifying key factors shaping their interactions. This sheds light on better seasonal influenza prediction and model construction, informing targeted prevention strategies and ultimately reducing the global burden of seasonal influenza.

Foodborne diseases have become a serious public health problem worldwide, and foodborne disease outbreaks have placed a heavy disease burden on China. Foodborne disease outbreaks occur most frequently among families in China. The objectives of this study were to analyze the cause of household foodborne disease outbreaks in China from 2010 to 2020 and to identify where preventive measures could be targeted. All data were obtained from the China Foodborne Disease Surveillance System Report. A total of 17,985 outbreaks, which resulted in 73,252 illnesses, 38,829 hospitalizations, and 1269 deaths, were reported in this period. Most household outbreaks of foodborne diseases occurred in May-October, and the highest number occurred in July (3620 outbreaks, 20%). The province with the highest number of outbreaks was Yunnan Province (4829 outbreaks), followed by Hunan Province (2264 outbreaks). The attribution analysis revealed that fungi (mainly poisonous mushrooms) were the most implicated food category, with 8873 (49.3%) cases. The second was poisonous plants and their products, with 1552 (8.6%) cases. Fungi were the primary etiologic agent, with 31,125 illnesses, accounting for 42.5% of the incidents. Inedibility and misuse (9423 outbreaks), unknown origin (2505 outbreaks), and improper processing (2365 outbreaks) were the main contributing factors causing outbreaks of foodborne diseases. The results show that southwest China was a high-risk area for household foodborne diseases. Therefore, public health institutions should strengthen supervision and food safety education of residents to reduce the outbreaks of household foodborne diseases.

Norovirus (NoV) is an important cause of viral acute gastroenteritis (AGE). To gain insights into the epidemiological characteristics and genetic diversity of NoV among children in Hubei, 1216 stool samples from children (≤ 5 years) obtained under AGE surveillance from January 2017 to December 2019 were analyzed. The results showed that NoV was responsible for 14.64% of AGE cases, with the highest detection rate in children aged 7-12 months (19.76%). Statistically significant differences were found between male and female infection rates (χ2 ​= ​8.108, P ​= ​0.004). Genetic analysis of RdRp and VP1 sequences showed that NoV GII genotypes were GII.4 Sydney [P31] (34.35%), GII.3 [P12] (25.95%), GII.2 [P16] (22.90%), GII.4 Sydney [P16] (12.98%), GII.17 [P17] (2.29%), GII.6 [P7] and GII.3 [P16] (each at 0.76%). GII.17 [P17] variants were divided into the Kawasaki323-like lineage and the Kawasaki308-like lineage. A unique recombination event was detected between strains of GII.4 Sydney 2012 and GII.4 Sydney 2016. Significantly, all GII.P16 sequences associated with GII.4/GII.2 obtained in Hubei were correlated with novel GII.2 [P16] variants that re-emerged in Germany in 2016. Antigenic site analysis of complete VP1 sequences from all GII.4 variants from Hubei identified notable variable residues of antibody epitopes. Genotyping under continuous AGE surveillance and observation of the antigenic sites of VP1 are important monitoring strategies for emerging NoV strains.

The COVID-19 pandemic has highlighted important considerations for modeling future pandemics.

To expand our understanding of the epidemiology of pigeon paramyxovirus type 1 (PPMV-1) in China, risk-based active surveillance was undertaken with pigeon swabs collected from live bird markets in 2014-2021. Seventy-six PPMV-1 strains were isolated from 12 provinces (60%) of the 20 provinces surveyed, and the positive rates of PPMV-1 varied from 0.50% to 3.19% annually. The complete genomic sequences of 18 representative viruses were analyzed, revealing a genome of 15,192 nucleotides, with the gene order 3\'-NP-P-M-F-HN-L-5\'. All isolates contained the 112RRQKRF117 cleavage site in the fusion (F) protein, a characteristic generally associated with virulent Newcastle disease viruses (NDVs), and the intracerebral pathogenicity index values (1.05-1.41) of four isolates indicated their virulence. A challenge experiment also demonstrated that all four isolates are pathogenic to pigeons, with morbidity rates of 60-100% and mortality rates of 0-30%. A further analysis of the functional domains of the F and HN proteins revealed several mutations in the fusion peptide, signal peptide, neutralizing epitopes, heptad repeat region, and transmembrane domains, and the substitution of cysteine residue 25 (C25Y) and substitutions in the HRb region (V287I) of the F protein and the transmembrane domain (V45A) of the HN protein may play important roles in PPMV-1 virulence. In a phylogenetic analysis based on the complete sequences of the F gene, all eighteen isolates all clustered into sub-genotype VI.2.1.1.2.2 (VIb) in class II, and shared high nucleotide sequence identity, indicating that the PPMV-1 strains in sub-genotype VI.2.1.1.2.2 are the predominant PPMV-1 viruses in pigeons in China and that the variations in these viruses have been relatively stable over the past 8 years. This study identifies the genetic and pathogenicity characteristics of the PPMV-1 strains prevalent in China and extends our understanding of the prevalence of this virus in China.