Evidence map›Paper›PMID 35916840›Full record

ArticleGlobal health action2022

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

Irene R Mremi, Calvin Sindato, Coleman Kishamawe, Susan F Rumisha, Sharadhuli I Kimera, Leonard E G Mboera

Abstract read
In one paragraph

Article in Global health action, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Irene R MremiSACIDS Foundation for One Health Sokoine University of Agriculture, Morogoro, Tanzania.ORCID 0000-0003-2578-7500
Calvin SindatoSACIDS Foundation for One Health Sokoine University of Agriculture, Morogoro, Tanzania.ORCID 0000-0003-3040-165X
Coleman KishamaweMwanza Research Centre, National Institute for Medical Research, Mwanza, Tanzania.ORCID 0000-0002-0670-9841
Susan F RumishaNational Institute for Medical Research, Headquarters, Dar es Salaam, Tanzania.ORCID 0000-0001-7058-488X
Sharadhuli I KimeraDepartment of Veterinary Medicine and Public Health, Sokoine University of Agriculture, Morogoro, Tanzania.ORCID 0000-0002-2295-0643
Leonard E G MboeraSACIDS Foundation for One Health Sokoine University of Agriculture, Morogoro, Tanzania.ORCID 0000-0001-5746-3776

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Data AnalysisDelivery of Health CareFemaleHumansMaleTanzaniadata analysis and useDisease surveillancedistrictearly warningTanzania

Identifiers

PMID35916840
PMCPMC9351552

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.