Cited by 88Malaria Research and ControlMobile Health and mHealth ApplicationsData-Driven Disease Surveillance

Rural health centres, communities and malaria case detection in Zambia using mobile telephones: a means to detect potential reservoirs of infection in unstable transmission conditions

Open access
Kamanga, Aniset, Moono, Petros, Stresman, Gillian, Mharakurwa, Sungano, Shiff, Clive·2010·Malaria Journal

Abstract

Background: Effective malaria control depends on timely acquisition of information on new cases, their location and their frequency so as to deploy supplies, plan interventions or focus attention on specific locations appropriately to intervene and prevent an upsurge in transmission. The process is known as active case detection, but because the information is time sensitive, it is difficult to carry out. In Zambia, the rural health services are operating effectively and for the most part are provided with adequate supplies of rapid diagnostic tests (RDT) as well as effective drugs for the diagnosis and treatment of malaria. The tests are administered to all prior to treatment and appropriate records are kept. Data are obtained in a timely manner and distribution of this information is important for the effective management of malaria control operations. The work reported here involves combining the process of positive diagnoses in rural health centres (passive case detection) to help detect potential outbreaks of malaria and target interventions to foci where parasite reservoirs are likely to occur. Methods: Twelve rural health centres in the Choma and Namwala Districts were recruited to send weekly information of rapid malaria tests used and number of positive diagnoses to the Malaria Institute at Macha using mobile telephone SMS. Data were entered in excel, expressed as number of cases per rural health centre and distributed weekly to interested parties. Results: These data from each of the health centres which were mapped using geographical positioning system (GPS) coordinates were used in a time sensitive manner to plot the patterns of malaria case detection in the vicinity of each location. The data were passed on to the appropriate authorities. The seasonal pattern of malaria transmission associated with local ecological conditions can be seen in the distribution of cases diagnosed. Conclusions: Adequate supplies of RDT are essential in health centres and the system can be expanded throughout the country to support strategic targeting of interventions by the National Malaria Control Programme. Participation by the health centre staff was excellent.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/1475-2875-9-96

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Understanding causal mechanisms is particularly relevant for complex interventions such as mHealth interventions, which are implemented in vastly different healthcare settings, use various functions of mobile phones, target widely different health conditions, and are used by persons with different backgrounds, behaviors, skills, and beliefs.

    “Understanding these mechanisms is particularly relevant for complex interventions, such as mHealth interventions, which are implemented in vastly different healthcare settings (varying from rural communities [13, 14] to major university hospitals [15]), use various functions of mobile phones (from text messaging [16–18] to picture transmission [19]), target widely different health conditions (from”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

The citation lists haven’t been fetched yet

References 8 · Cited by 88

Research works printed but not linked: 1

  1. Taylor P Taputaira A Forty years of malaria control in Zimbabwe 1988 Zimbabwe Scientific Association. First National Symposium of Science and Technology

Authors
Kamanga, A., Moono, P., Stresman, G., Mharakurwa, S., & Shiff, C.
Affiliations
Johns Hopkins University (US)
Corresponding author
Shiff, Clive
Venue
Malaria Journal
Published
2010-04-15
Volume
9
Issue
1
Pages
96-96
ISSN
1475-2875 (ISSN-L)
OpenAlex
W2124614270
Cited by
88
References
8
Citations by year
2026: 1 · 2025: 3 · 2024: 9 · 2023: 2 · 2022: 8 · 2021: 2 · 2020: 5 · 2019: 5 · 2018: 3 · 2017: 8 · 2016: 7 · 2015: 5 · 2014: 12 · 2013: 5 · 2012: 7
FWCI
5.73
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Malaria Journal (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
Johns Hopkins University
Topics
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Malaria Research and Control
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Medicine › Epidemiology › Data-Driven Disease Surveillance
Keywords
malaria case detection, rapid diagnostic tests, malaria surveillance, malaria control, parasite reservoir, malaria outbreak, rural health facilities, seasonal malaria transmission, intervention targeting, Zambia
MeSH terms
Antimalarials, Data Collection, Diagnostic Tests, Routine, Disease Reservoirs, Health Workforce, Humans, Malaria, Reagent Kits, Diagnostic, Rural Health, Seasons, Time Factors, Zambia, Incidence, Rural Health Services, Geographic Information Systems, Cell Phone

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review