Improving disease surveillance data analysis, interpretation, and use at the district level in Tanzania

Glob Health Action. 2022 Dec 31;15(1):2090100. doi: 10.1080/16549716.2022.2090100.

Abstract

An effective disease surveillance system is critical for early detection and response to disease epidemics. This study aimed to assess the capacity to manage and utilize disease surveillance data and implement an intervention to improve data analysis and use at the district level in Tanzania. Mapping, in-depth interview and desk review were employed for data collection in Ilala and Kinondoni districts in Tanzania. Interviews were conducted with members of the council health management teams (CHMT) to assess attitudes, motivation and practices related to surveillance data analysis and use. Based on identified gaps, an intervention package was developed on basic data analysis, interpretation and use. The effectiveness of the intervention package was assessed using pre-and post-intervention tests. Individual interviews involved 21 CHMT members (females = 10; males = 11) with an overall median age of 44.5 years (IQR = 37, 53). Over half of the participants regarded their data analytical capacities and skills as excellent. Analytical capacity was higher in Kinondoni (61%) than Ilala (52%). Agreement on the availability of the opportunities to enhance capacity and skills was reported by 68% and 91% of the participants from Ilala and Kinondoni, respectively. Reported challenges in disease surveillance included data incompleteness and difficulties in storage and accessibility. Training related to enhancement of data management was reported to be infrequently done. In terms of data interpretation and use, despite reporting of incidence of viral haemorrhagic fevers for five years, no actions were taken to either investigate or mitigate, indicating poor use of surveillance data in monitoring disease occurrence. The overall percentage increase on surveillance knowledge between pre-and post-training was 37.6% for Ilala and 20.4% for Kinondoni indicating a positive impact on of the training. Most of CHMT members had limited skills and practices on data analysis, interpretation and use. The training in data analysis and interpretation significantly improved skills of the participants.

Keywords: Disease surveillance; Tanzania; data analysis and use; district; early warning.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Data Analysis*
  • Delivery of Health Care*
  • Female
  • Humans
  • Male
  • Tanzania / epidemiology

Grants and funding

This study is part of a larger project, Pan African Network for Rapid Research, Response, Relief and Preparedness for Infectious Disease Epidemic, with financial support from the (EDCTP2) programme (Grant RIA2016E-1609) which is supported under Horizon 2020, the European Union’s Framework Programme for Research and Innovation. IRM is a PhD student supported by the Government of the United Republic of Tanzania through the World Bank (World Bank Group WB-ACE II Grant; PAD1436, IDA Credit 5799-TZ) to the SACIDS Africa Centre of Excellence for Infectious Diseases of Humans and Animals in East and Southern Afric; European and Developing Countries Clinical Trials Partnership.