Fred Nsubuga

Sensitivity and positive predictive value of the measles surveillance system in Uganda, 2012-2015

Introduction : disease surveillance is a critical component in the control and elimination of vaccine preventable diseases. The Uganda National Expanded Program on Immunization strives to have a sensitive surveillance system within the Integrated Disease Surveillance and Response (IDSR) framework. We analyzed measles surveillance data to determine the effectiveness of the measles case-based surveillance system and estimate its positive predictive value in order to inform policy and practice. Methods : an IDSR alert was defined as 1 suspected measles case reported by a district in a week, through the electronic Health Management Information System. We defined an alert in the measles case-based surveillance system (CBS) as 1 suspected measles case with a blood sample collected for confirmation during the corresponding week in a particular district. Effectiveness of CBS was defined as having 80% of IDSR alerts with a blood sample collected for laboratory confirmation. Positive predictive value was defined as the proportion of measles case-patients who also had a positive measles serological result (IgM +). We reviewed case-based surveillance data with laboratory confirmation and measles surveillance data from the electronic Health Management Information System from 2012-2015. Results : a total of 6,974 suspected measles case-persons were investigated by the measles case-based surveillance between 2012 and 2015. Of these, 943 (14%) were measles specific IgM positive. The median age of measles case-persons between 2013 and 2015 was 4.0 years. Between 2013 and 2015, 72% of the IDSR alerts reported in the electronic Health Management Information System, had blood samples collected for laboratory confirmation. This was however less than the WHO recommended standard of 80%. The PPV of CBS between 2013 and 2015 was 8.6%. Conclusion : effectiveness of measles case-based surveillance was sub-optimal, while the PPV showed that true measles cases have significantly reduced in Uganda. We recommended strengthening of case-based surveillance to ensure that all suspected measles cases have blood samples collected for laboratory confirmation to improve detection and ensure elimination by 2020.

Investigating an outbreak of measles in Kamwenge District, Uganda, July 2015

Globalization has opened many fronts for disease outbreaks because of the quick movement of people and porous borders around the world. The emergence of zoonotic diseases and other communicable diseases highlights the need for implementation of the Global Health Security Agenda packages if countries are to achieve compliance with International Health Regulations (IHR 2005). Health workforce development is one of the critical components that must be addressed with utmost urgency if gaps in early disease detection and response are to be addressed. In this regard, this case study is based on a measles outbreak investigation in Uganda simulating a real-life outbreak investigation by field epidemiologists and seeks to demonstrate the principles of applied epidemiology outlining the critical steps in outbreak investigations and generation of evidence for decision making. It aims to shore up the health workforce capacity by providing practical training for field epidemiology students and professionals that builds their skills in outbreak investigation. This case study can be completed in less than three hours.

Factors that affect immunization data quality in Kabarole District, Uganda

Introduction Reliable and timely immunization data is vital at all levels of health care to inform decisions and improve program performance. Inadequate data quality may impair our understanding of the true vaccination coverage and also hinder our capability to meet the program objectives. It’s therefore important to regularly assess immunization data quality to ensure good performance, sound decision making and efficient use of resources. Methods We conducted an immunization data quality audit between July and August 2016. The verification factor was estimated by dividing the recounted diphtheria, pertussis and tetanus third dose vaccination for children under 1 year (DPT3<1 year) by reported DPT3<1 year. The quality of data collection processes was measured using quality indices for the 3 different components: recording practices, storage/reporting, monitoring and evaluation. These indices were applied to the different levels of the health care service delivery system. Quality index score was estimated by dividing the total question or observation correctly answered by the total number of answers/ observations for a particular component. Results The mean health center verification factor was 87%. Sixty five percent (32/49) of the health centers had consistent data, 27% (13/49) over reported and 4% (2/49) under-reported. Health center 11s and 111s contributed to over-reporting and under-reporting. All the health centers’ reports were complete and timely between January and June and from November to December. The mean quality indices for the 3 different componets assessed were; recording practices 66%, storing/reporting 75%, monitoring and evaluation 43%. There was a weak positive correlation between the health center verifaction factor and quality index though this was not statistically significant (r = 0.014; p = 0.92). Conclusion Lower level health centers contributed significantly to the inconsistencies in immunization data; there were wide variation between the quality indices of recording practices, storage/reporting, monitoring and evaluation. We recommended that District Local Governments and Ministry of Health focus on improving data quality at lower levels of health service delivery.

Positive predictive value and effectiveness of measles case-based surveillance in Uganda, 2012-2015

Introduction Disease surveillance is a critical component in the control and elimination of vaccine preventable diseases. The Uganda National Expanded Program on Immunization strives to have a sensitive surveillance system within the Integrated Disease Surveillance and Response (IDSR) framework. We analyzed measles surveillance data to determine the effectiveness of the measles case-based surveillance system and estimate its positive predictive value in order to inform policy and practice. Methods An IDSR alert was defined as ≥1 suspected measles case reported by a district in a week, through the electronic Health Management Information System. We defined an alert in the measles case-based surveillance system (CBS) as ≥1 suspected measles case with a blood sample collected for confirmation during the corresponding week in a particular district. Effectiveness of CBS was defined as having ≥80% of IDSR alerts with a blood sample collected for laboratory confirmation. Positive predictive value was defined as the proportion of measles case-patients who also had a positive measles serological result (IgM +). We reviewed case-based surveillance data with laboratory confirmation and measles surveillance data from the electronic Health Management Information System from 2012–2015. Results A total of 6,974 suspected measles case-persons were investigated by the measles case-based surveillance between 2012 and 2015. Of these, 943 (14%) were measles specific IgM positive. The median age of measles case-persons between 2013 and 2015 was 4.0 years. Between 2013 and 2015, 72% of the IDSR alerts reported in the electronic Health Management Information System, had blood samples collected for laboratory confirmation. This was however less than the WHO recommended standard of ≥80%. The PPV of CBS between 2013 and 2015 was 8.6%. Conclusion In conclusion, the effectiveness of measles case-based surveillance was sub-optimal, while the PPV showed that true measles cases have significantly reduced in Uganda. We recommended strengthening of case-based surveillance to ensure that all suspected measles cases have blood samples collected for laboratory confirmation to improve detection and ensure elimination by 2020.