Evidence map›Paper›PMID 33685454›Full record

ArticleMalaria journal2021

Digitized smart surveillance and micromanagement using information technology for malaria elimination in Mangaluru, India: an analysis of five-year post-digitization data.

B Shantharam Baliga, Shrikala Baliga, Animesh Jain, Naveen Kulal, Manu Kumar, Naren Koduvattat, B G Prakash Kumar, Arun Kumar, Susanta K Ghosh

Open access · goldAbstract read
In one paragraph

Article in Malaria journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.2field-weighted citation impact, top 22% of its field
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

6 citing papers in PubMed, 11 citations in OpenAlex.

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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

9 authors at 3 institutions in 1 country.

B Shantharam BaligaKasturba Medical College Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, India.
Shrikala BaligaKasturba Medical College Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, India.
Animesh JainKasturba Medical College Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, India.
Naveen KulalDepartment of Public Health, Dakshina Kannada District, Mangalore, Karnataka, 575001, India.
Manu KumarOfficer On Special Duty, Chief Minister's Secretariat Bengaluru, Bangalore, Karnataka, 560001, India.
Naren KoduvattatI-Point Consulting, Punja Arcade, Lalbagh, Mangalore, Karnataka, 575003, India.
B G Prakash KumarDirectorate of Health and Family Welfare Services, Government of Karnataka, Bangalore, Karnataka, 560009, India.
Arun KumarGeneral Hospital, Shikaripura, Karnataka, 577427, India.
Susanta K GhoshICMR-National Institute of Malaria Research (Field Unit), Nirmal Bhawan, ICMR Campus, Poojanahalli, Kannamangla Post, Devanahalli Taluk, Bangalore, Karnataka, 562110, India. ghoshnimr@gmail.com.ORCID http://orcid.org/0000-0001-8964-3034
Manipal Academy of Higher Education · INGovernment of Karnataka · INS.R. Kalla Memorial Gastro and General Hospital · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMalaria control system (MCS), an Information technology (IT)-driven surveillance and monitoring intervention is being adopted for elimination of malaria in Mangaluru city, Karnataka, India since October 2015. This has facilitated 'smart surveillance' followed by required field response within a timeline. The system facilitated data collection of individual case, data driven mapping and strategies for malaria elimination programme. This paper aims to present the analysis of post-digitization data of 5 years, discuss the current operational functionalities of MCS and its impact on the malaria incidence.

methodsIT system developed for robust malaria surveillance and field response is being continued in the sixth year. Protocol for surveillance control was followed as per the national programme guidelines mentioned in an earlier publication. Secondary data from the malaria control system was collated and analysed. Incidence of malaria, active surveillance, malariogenic conditions and its management, malariometric indices, shrinking malaria maps were also analysed.

resultsSmart surveillance and subsequent response for control was sustained and performance improved in five years with participation of all stakeholders. Overall malaria incidence significantly reduced by 83% at the end of 5 years when compared with year of digitization (DY) (p < 0.001). Early reporting of new cases (within 48 h) was near total followed by complete treatment and vector control. Slide positivity rate (SPR) decreased from 10.36 (DY) to 6.5 (PDY 5). Annual parasite incidence (API) decreased from 16.17 (DY) to 2.64 (PDY 5). There was a negative correlation between contact smears and incidence of malaria. Five-year data analyses indicated declining trends in overall malaria incidence and correlation between closures by 14 days. The best impact on reduction in incidence of malaria was recorded in the pre-monsoon months (~ 85%) compared to lower impact in July-August months (~ 40%).

conclusionMCS helped to micromanage control activities, such as robust reporting, incidence-centric active surveillance, early and complete treatment, documentation of full treatment of each malaria patient, targeted mosquito control measures in houses surrounding reported cases. The learnings and analytical output from the data helped to modify strategies for control of both disease and the vector, heralding the city into the elimination stage.

Indexed as

Data ManagementDisease EradicationHumansIndiaInformation TechnologyMalariaPopulation SurveillanceSeasonsDigitizationGISInformation technologyMalariaMalaria eliminationMangaluruMicromanagementSmart surveillanceTAB

Identifiers

PMID33685454
PMCPMC7938374
OpenAlexW3133943293

What OpenQuestion holds

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LicenceCC BY
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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.