背景:南非设定了到2023年消除疟疾的目标,夸祖鲁-纳塔尔省是最接近实现这一目标的疟疾流行省。国家消除疟疾战略计划(NMESP)的两个目标侧重于加强监测系统,以支持国家的消除努力。针对NMESP目标的目标定期评估疟疾监测系统对于改善其绩效和影响至关重要。本研究旨在评估夸祖鲁-纳塔尔省的疟疾监测系统是否符合NMESP监测目标。
方法:使用混合方法横断面研究设计来评估疟疾监测系统,重点是地区卫生信息系统2(DHIS2)。该研究评估了数据质量,及时性、及时性简单,和系统的可接受性。KZN省疟疾控制计划的关键人员使用自我管理问卷进行了访谈,以评估他们对该系统的简单性和可接受性的看法。从DHIS2中提取2016年1月至2020年12月的疟疾病例数据,并评估数据质量和及时性。
结果:调查受访者普遍认为基于DHIS2的监测系统可以接受(79%,11/14)且易于使用(71%,10/14),说明他们很容易找到,Extract,并共享数据(64%,9/14).总体数据质量良好(88.9%),尽管病例分类所需的一些变量的完整性和数据可用性较低.然而,案件通知不及时,只有61%(2622/4329)的病例在诊断后24小时内通知。在5年的学习期间,DHIS2记录了4333例疟疾病例。大多数病例(81%,3489/4330)被归类为进口,主要是男性(67%,2914/4333)。
结论:虽然KZN省的疟疾监测系统在很大程度上达到了NMESP监测战略目标,它未能实现在诊断后24小时内100%通知病例的总体监测目标。KZN省报告的大多数病例被归类为进口病例,强调完整数据对准确病例分类的重要性。需要与负责病例通知的医疗保健专业人员合作,并将汇总数据传回给他们,以鼓励和提高通知的及时性。
BACKGROUND: South Africa set a target to eliminate malaria by 2023, with KwaZulu-Natal (KZN) Province the malaria-endemic province closest to achieving this goal. Objective two of the National Malaria Elimination Strategic Plan (NMESP) focused on strengthening surveillance systems to support the country\'s elimination efforts. Regular evaluations of the malaria surveillance systems against the targets of the NMESP objective are crucial in improving their performance and impact. This study aimed to assess whether the malaria surveillance system in KwaZulu-Natal Province meets the NMESP surveillance objective and goals.
METHODS: A mixed-methods cross-sectional study design was used to evaluate the malaria surveillance system, focusing on the District Health Information System 2 (DHIS2). The study assessed the data quality, timeliness, simplicity, and acceptability of the system. Key personnel from KZN\'s Provincial malaria control programme were interviewed using self-administered questionnaires to evaluate their perception of the system\'s simplicity and acceptability. Malaria
case data from January 2016 to December 2020 were extracted from the DHIS2 and evaluated for data quality and timeliness.
RESULTS: The survey respondents generally found the DHIS2-based surveillance system acceptable (79%, 11/14) and easy to use (71%, 10/14), stating that they could readily find, extract, and share data (64%, 9/14). Overall data quality was good (88.9%), although some variables needed for
case classification had low completeness and data availability. However,
case notifications were not timely, with only 61% (2 622/4 329) of cases notified within 24 h of diagnosis. During the 5-year study period, the DHIS2 captured 4 333 malaria cases. The majority of cases (81%, 3 489/4 330) were categorized as imported, and predominately in males (67%, 2 914/4 333).
CONCLUSIONS: While the malaria surveillance system in KZN Province largely met the NMESP surveillance strategic goals, it failed to achieve the overarching surveillance objective of 100% notification of cases within 24 h of diagnosis. The majority of reported cases in KZN Province were classified as imported, emphasizing the importance of complete data for accurate
case classification. Engaging with healthcare professionals responsible for
case notification and disseminating aggregated data back to them is needed to encourage and improve notification timeliness.