{"id":25501,"date":"2024-03-29T04:27:00","date_gmt":"2024-03-28T20:27:00","guid":{"rendered":"http:\/\/csccm.org.cn\/?p=25501"},"modified":"2024-03-29T05:53:41","modified_gmt":"2024-03-28T21:53:41","slug":"lancet-glob-health%e5%8f%91%e8%a1%a8%e8%bf%b0%e8%af%84%ef%bc%9a%e9%9d%9e%e6%b4%b2%e7%9a%84%e7%bb%86%e8%8f%8c%e8%80%90%e8%8d%af%e8%b4%9f%e6%8b%85%ef%bc%9a%e5%87%86%e7%a1%ae%e6%80%a7%ef%bc%8c%e8%a1%8c","status":"publish","type":"post","link":"https:\/\/csccm.org.cn\/?p=25501","title":{"rendered":"[Lancet Glob Health\u53d1\u8868\u8ff0\u8bc4]\uff1a\u975e\u6d32\u7684\u7ec6\u83cc\u8010\u836f\u8d1f\u62c5\uff1a\u51c6\u786e\u6027\uff0c\u884c\u52a8\u4ee5\u53ca\u5176\u4ed6"},"content":{"rendered":"\n

COMMENT|ONLINE FIRST<\/a><\/p>\n\n\n\n

Bacterial antimicrobial resistance burden in Africa: accuracy, action, and alternatives<\/h1>\n\n\n\n

Sabiha Y Essack, <\/a>Annick Lenglet<\/h3>\n\n\n\n

Lancet Glob Health Published: December 19, 2023<\/h3>\n\n\n\n

DOI:https:\/\/doi.org\/10.1016\/S2214-109X(23)00587-9<\/a><\/h3>\n\n\n\n

Understanding the burden of antimicrobial resistance (AMR), detecting potential hospital outbreaks due to multidrug resistant-bacteria, and monitoring local, regional, and global trends of bacterial resistance for the early warning of emerging or escalating AMR depend on high-quality surveillance systems that generate representative, quality-assured AMR data. Representativeness and quality of surveillance data are particularly important if used for clinical decision making, assessing the impact of AMR mitigation interventions, and formulating health investment cases for stewardship and infection prevention and control (IPC) programmes. Microbiological laboratories are the primary source of these data.<\/p>\n\n\n\n

In\u00a0The Lancet Global Health,<\/em>\u00a0Mohsen Naghavi and colleagues1<\/a><\/sup> estimate the burden of bacterial AMR in the WHO African region extracted from the global burden of bacterial AMR study in 2019.2<\/a><\/sup><\/p>\n\n\n\n

The modelling was conducted on microbiological data from clinical and surveillance databases and national antimicrobial consumption data. The findings reconfirm that bacterial AMR forms a substantial burden for the current and future public health of the continent.2<\/a><\/sup>\u00a0As potentially useful as these findings might be, these data present an incomplete picture of AMR and antimicrobial consumption in African countries, and the utility of the results must be considered in this context. For example, findings from the\u00a0Mapping AMR and AMU Partnership<\/em>\u00a0(MAAP), a Fleming Fund project that reviewed 819\u2009584 AMR records from 205 laboratories in 14 African countries, revealed that just 1\u00b73% of laboratories undertook bacteriological testing, 80% had conducted fewer than 1000 antimicrobial susceptibility tests annually, and only a third of the pathogens on the WHO bacterial priority pathogen list were consistently tested in these countries.3<\/a><\/sup>\u00a0A systematic review of AMR surveillance systems in Africa reported that although almost half of African countries analysed (23 of 47) had established national AMR surveillance systems, the AMR data generated were of potentially limited utility for policy or clinical practice action because of suboptimal data reliability and validity based on the lack of methodological rigour, particularly with regard to external quality assurance and the absence of epidemiological data and metadata.4<\/a><\/sup><\/p>\n\n\n\n

The surveillance data used in the study by Naghavi and colleagues1<\/a><\/sup> was largely sourced from conventional, laboratory-based surveillance systems that are contingent on the availability of human, infrastructural, and operational resources, and human resource capacity and competence. Conventional surveillance is biased to better-resourced hospitals and urban settings, and is not feasible in resource-constrained settings, necessitating alternative sources of surveillance data. For example, wastewater surveillance for polio and SARS-CoV-2 provides information on the geographical spread and magnitude of viral circulation in communities as well as early warning of outbreaks.5<\/a><\/sup>\u00a0Research on wastewater surveillance of AMR as an alternative cost-effective, reliable, representative proxy for conventional AMR surveillance at the population level is underway. For example, antibiotic resistance in\u00a0Escherichia coli<\/em>\u00a0from municipal wastewater was correlated with resistance in urinary\u00a0E coli<\/em>isolates at primary care level (r<\/em>2<\/sup>=0\u00b782) in Sweden.6<\/a><\/sup>\u00a0Similarly, the global sewage project that monitors antibiotic resistance genes (ARGs) in sewage showed systematic differences in ARG abundance and diversity between countries, with low-income and middle-income countries showing higher ARG levels. Resistance was better associated with socioeconomic factors such as poor water, sanitation, and hygiene (WaSH) compared with antibiotic use.6<\/a><\/sup>\u00a0While sewage or wastewater-based AMR surveillance might also be biased to urban areas with developed sewage systems, such data potentially reflect clinical and community AMR and provide an alternative cost-effective surveillance system at population level.7<\/a><\/sup><\/p>\n\n\n\n

Furthermore, we have shown that routine clinical data on neonatal sepsis incidence within neonatal units without access to microbiological diagnostics could be leveraged to provide early warning for outbreaks.8<\/a><\/sup>\u00a0Similar proxy indicators for AMR prevalence and burden could be generated from other health facility data (length of stay for infection, readmissions) or other public health programmes (vaccination coverage, safe water coverage, etc).<\/p>\n\n\n\n

Notwithstanding the concerns regarding data quality and the need for alternative or supplementary AMR surveillance systems, indiscriminate antibiotic prescription and use, inadequate IPC in health-care facilities, and suboptimal WaSH in communities are known drivers for the development and transmission of AMR. There are several evidence-based interventions to optimise appropriate use and prevent or contain infection that can be adapted and adopted in country contexts using implementation research, which in AMR involves the quantitative and qualitative scientific validation of processes that will facilitate the systematic and sustainable uptake of evidence-based AMR interventions into routine practice in order to strengthen health system capacity to mitigate AMR.9<\/a><\/sup><\/p>\n","protected":false},"excerpt":{"rendered":"

COMMENT|ONLINE FIRST Bacterial antimicrobial resistance […]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[24,23],"tags":[],"_links":{"self":[{"href":"https:\/\/csccm.org.cn\/index.php?rest_route=\/wp\/v2\/posts\/25501"}],"collection":[{"href":"https:\/\/csccm.org.cn\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/csccm.org.cn\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/csccm.org.cn\/index.php?rest_route=\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/csccm.org.cn\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=25501"}],"version-history":[{"count":1,"href":"https:\/\/csccm.org.cn\/index.php?rest_route=\/wp\/v2\/posts\/25501\/revisions"}],"predecessor-version":[{"id":25502,"href":"https:\/\/csccm.org.cn\/index.php?rest_route=\/wp\/v2\/posts\/25501\/revisions\/25502"}],"wp:attachment":[{"href":"https:\/\/csccm.org.cn\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=25501"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/csccm.org.cn\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=25501"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/csccm.org.cn\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=25501"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}