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Chronic kidney disease is now recognized to be a worldwide problem associated with significant morbidity and mortality and there is a steep increase in the number of patients reaching end-stage renal disease. In many parts of the world, the disease affects younger people without diabetes or hypertension. The costs to family and society can be enormous. Early recognition of CKD may help prevent disease progression and the subsequent decline in health and longevity. Surveillance programs for early CKD detection are beginning to be implemented in a few countries. In this article, we will focus on the challenges and successes of these programs with the hope that their eventual and widespread use will reduce the complications, deaths, disabilities, and economic burdens associated with CKD worldwide.

By coupling long-range polymerase chain reaction, wastewater-based epidemiology, and pathogen sequencing, we show that adenovirus type 41 hexon-sequence lineages, described in children with hepatitis of unknown origin in the United States in 2021, were already circulating within the country in 2019. We also observed other lineages in the wastewater, whose complete genomes have yet to be documented from clinical samples.

Human noroviruses (HNoVs) are a leading cause of acute gastroenteritis worldwide, with significant public health implications. In this study, wastewater-based epidemiology (WBE) was used to monitor the circulation and genetic diversity of HNoVs in Rome over an eight-year period (2017–2024). A total of 337 wastewater samples were analyzed using RT-nested PCR and next-generation sequencing (NGS) to identify genogroups GI and GII and their respective genotypes. The results showed that GII had higher detection rates (66.5%) compared to GI (50.7%), with significant variation between years. Detection rates peaked in 2019 before declining sharply in 2020, coinciding with the COVID-19 pandemic and rebounding after the pandemic in 2023. A total of 24 genotypes were identified (8 GI and 17 GII), including persistent variants GII.2, GII.3 and GII.4 and emerging genotypes such as GII.8, GII.10 and GII.14. Only two GII.4 variants, Sydney_2016 and Sydney_2012, were detected in the study. These results demonstrate the utility of WBE in tracking HNoVs circulation, identifying genotype diversity and capturing shifts in transmission dynamics. WBE provides a cost-effective and comprehensive tool for public health surveillance, particularly in regions with limited clinical surveillance. Sustained investment in WBE is crucial for advancing our understanding of HNoVs epidemiology and its long-term trends.

Background Since its first report in 2007, avian influenza (AI) has been endemic in Bangladesh. While live poultry marketing is widespread throughout the country and known to influence AI dissemination and persistence, trading patterns have not been described. The aim of this study is to assess poultry trading practices and features of the poultry trading networks which could promote AI spread, and their potential implications for disease control and surveillance. Data on poultry trading practices was collected from 849 poultry traders during a cross-sectional survey in 138 live bird markets (LBMs) across 17 different districts of Bangladesh. The quantity and origins of traded poultry were assessed for each poultry type in surveyed LBMs. The network of contacts between farms and LBMs resulting from commercial movements of live poultry was constructed to assess its connectivity and to identify the key premises influencing it. Results Poultry trading practices varied according to the size of the LBMs and to the type of poultry traded. Industrial broiler chickens, the most commonly traded poultry, were generally sold in LBMs close to their production areas, whereas ducks and backyard chickens were moved over longer distances, and their transport involved several intermediates. The poultry trading network composed of 445 nodes (73.2% were LBMs) was highly connected and disassortative. However, the removal of only 5.6% of the nodes (25 LBMs with the highest betweenness scores), reduced the network’s connectedness, and the maximum size of output and input domains by more than 50%. Conclusions Poultry types need to be discriminated in order to understand the way in which poultry trading networks are shaped, and the level of risk of disease spread that these networks may promote. Knowledge of the network structure could be used to target control and surveillance interventions to a small number of LBMs.

Highly pathogenic avian influenza (HPAI) viruses continue to circulate worldwide, causing numerous outbreaks among bird species and severe public health concerns. H5N1 and H5N8 are the two most fundamental HPAI subtypes detected in birds in the last two decades. The two viruses may compete with each other while sharing the same host population and, thus, suppress the spread of one of the viruses. In this study, we performed a statistical analysis to investigate the temporal correlation of the HPAI H5N1 and HPAI H5N8 subtypes using globally reported data in 2015–2020. This was joined with an in-depth analysis using data generated via our national surveillance program in Egypt. A total of 6412 outbreaks were reported worldwide during this period, with 39% (2529) as H5N1 and 61% (3883) as H5N8. In Egypt, 65% of positive cases were found in backyards, while only 12% were found in farms and 23% in live bird markets. Overall, our findings depict a trade-off between the number of positive H5N1 and H5N8 samples around early 2017, which is suggestive of the potential replacement between the two subtypes. Further research is still required to elucidate the underpinning mechanisms of this competitive dynamic. This, in turn, will implicate the design of effective strategies for disease control.

Influenza D virus (IDV), which is a new member of the Orthomyxoviridae family, is potentially involved in bovine respiratory diseases (BRDs). Bovine IDVs (BIDVs) from Japan have been distributed nationwide since 2010 and are genetically distinct from foreign IDVs. We isolated BIDVs from three BRD outbreaks, in Hokkaido during 2018–2020, to understand their genetic and antigenic characteristics. Retrospective surveillance was performed using sera collected throughout the last decade in Hokkaido to investigate BIDV existence. Three BIDVs were isolated using cell culture. Comparative and phylogenetic analyses using sequence data of the three BIDVs and IDVs from Japan and other countries available in GenBank demonstrated that Japanese BIDVs, including the three BIDV isolates, were genetically distinct from other IDVs. Genotype classifications based on the rotavirus genotype classification revealed multiple genotypes of RNA segments 1–7. Two BIDVs were of a new genotype, different from those of other Japanese BIDVs. Neutralization assays against two BIDVs with different genotypes using sera collected in acute and recovery phases of BRD revealed differences in cross-reactivity to heterogenous BIDVs. Retrospective surveillance suggested that BIDV existed in Hokkaido, in 2009. Our findings suggest that BIDVs of different genotypes and antigenicity are distributed and maintained in Hokkaido and provide new insights into molecular characteristics and the evolution of IDVs.

Persons living in long-term care facilities (LTCFs) were disproportionately affected by COVID-19. We used wastewater surveillance to detect SARS-CoV-2 infection in this setting by collecting and testing 24-hour composite wastewater samples 2-4 times weekly at 6 LTCFs in Kentucky, USA, during March 2021-February 2022. The LTCFs routinely tested staff and symptomatic and exposed residents for SARS-CoV-2 using rapid antigen tests. Of 780 wastewater samples analyzed, 22% (n = 173) had detectable SARS-CoV-2 RNA. The LTCFs reported 161 positive (of 16,905) SARS-CoV-2 clinical tests. The wastewater SARS-CoV-2 signal showed variable correlation with clinical test data; we observed the strongest correlations in the LTCFs with the most positive clinical tests (n = 45 and n = 58). Wastewater surveillance was 48% sensitive and 80% specific in identifying SARS-CoV-2 infections found on clinical testing, which was limited by frequency, coverage, and rapid antigen test performance.

In the eastern Tibetan plateau both human cystic and alveolar echinococcosis (AE) caused by infection with Echincoccus granulosus or Echinococcus multilocularis, respectively are highly endemic. The domestic dog plays a key role in zoonotic transmission in this region. Our primary objective was to investigate the role of domestic dogs in maintaining transmission of E. multilocularis in Shiqu county, Sichuan. A cohort of 281 dogs was followed up over one year after a single treatment with praziquantel followed by re-infection surveillance at 2, 5 and 12 months post-treatment. Faecal samples were tested by an Echinococcus genus-specific coproantigen ELISA and two species-specific copro-PCR tests. Total Echinococcus coproantigen prevalence in Shiqu at baseline was 21% and 9·6% after 2 months. E. multilocularis copro-PCR was positive in 11·2% of dogs before treatment (vs 3·6% with E. granulosus copro-DNA), 2·9% at 2 months post-treatment, and 0% at 5 month and 12 months. The results suggest that dogs may have the potential to maintain E. multilocularis transmission within local pastoral communities, and thus dog dosing could be an effective strategy to reduce transmission of E. multilocularis as well as E. granulosus in these co-endemic Tibetan communities.

Many studies have explored social media and users search activities such as Google Trends to predict and detect influenza activities. Studies that examined Google Trends correlation with the actual hospital influenza cases were conducted in non-tropical regions that have clearly defined seasons. Tropical areas are known for having less-defined seasonality and the extent of Google Trends concordance with actual influenza cases is unknown for these areas. The goal of this study is to compare Google Trends with hospital cases in tropical regions. We analyzed 48,263 influenza cases in the time period of 2010 to 2019. The cases were retrieved from central hospital medical records in tropical regions using the corresponding codes for influenza ICD-10 AM. Cases from the medical records were compared with Google Trends to determine trends, seasonality, and correlation. Graphically, there were some similar areas of the trend, but cross-correlation analysis did not show any significant correlation between hospital and Google Trends with a maximum correlation rate of 0.300. Seasonality analysis showed a clear pattern that peaked around November in Google Trends while hospital data showed less defined seasonality with a smaller peak occurring at the end of December and beginning of January. Based on the results, there is a weak correlation between Google Trends and hospital data. More innovative methods are emerging to predict influenza activity using social media and user search data and further study is needed to examine the concurrent trends derived using these methods across regions that have different humidity levels and temperatures.

As Covid-19 cases accelerate or plateau around the world, we urgently need a point-of-care test that is inexpensive enough to use frequently, even if it lacks high analytic sensitivity. Such a testing regimen would allow us to detect infections in time to act.