See the published version of this article at Malaria Journal.
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Methodology
Susanta Kumar Ghosh
National Institute of Malaria Research Field Station Bangalore
Corresponding Author
ORCiD: https://orcid.org/0000-0001-8964-3034
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at Malaria Journal.
Background
Malaria 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 facilitated ‘smart surveillance’ followed by required field response within a timeline. The system facilitated data collection of individual case and 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.
Methods
IT system developed for robust malaria surveillance and field response is being continued in the 6th year. Protocol for surveillance control was followed as per the national programme guidilines mentioned earlier. Secondary data from the malaria control system is collated and analysed. Incidence of malaria, active surveillance, malariogenic conditions and its management, malariometric indices, shrinking malaria map were also analysed.
Results
Smart 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 digitizarion (DY) (p<0.001). Early reporting of new cases (within 48 hrs) 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 closure by 14 days. The best impact on reduction in incidence of malaria was recorded in pre-monsoon months (~85%) compared to lower impact in July-August months (~40%).
Conclusion
IT System 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.
Keywords
Malaria, Digitization, GIS, TAB, Smart surveillance, Micromanagement, Malaria elimination, Information technology, Mangaluru
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CURRENT STATUS: Published
Version (no preprint)
Posted 08 Feb, 2021
Editorial decision: Minor Revision
On 08 Feb, 2021
Reviewer #2 agreed
On 07 Feb, 2021
Review #2 received
Received 07 Feb, 2021
Review #1 received
Received 07 Feb, 2021
Reviewer #1 agreed
On 01 Feb, 2021
Editor assigned
On 26 Jan, 2021
Reviewers invited
Invitations sent on 26 Jan, 2021
Submission checks complete
On 26 Jan, 2021
Editor invited
On 26 Jan, 2021
This version was not preprinted
Version 1
Posted 29 Dec, 2020
Published
On 08 Mar, 2021
No community comments so far
Editorial decision: Major Revision
On 11 Jan, 2021
Reviewer #2 agreed
On 10 Jan, 2021
Review #2 received
Received 10 Jan, 2021
Review #1 received
Received 10 Jan, 2021
Reviewer #1 agreed
On 30 Dec, 2020
Reviewers invited
Invitations sent on 29 Dec, 2020
Editor assigned
On 23 Dec, 2020
Submission checks complete
On 23 Dec, 2020
Editor invited
On 23 Dec, 2020
First submitted
On 21 Dec, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Infectious Diseases
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This preprint is under consideration at Malaria Journal. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Methodology
Susanta Kumar Ghosh
National Institute of Malaria Research Field Station Bangalore
Corresponding Author
ORCiD: https://orcid.org/0000-0001-8964-3034
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
Version (no preprint)
Posted 08 Feb, 2021
Editorial decision: Minor Revision
On 08 Feb, 2021
Reviewer #2 agreed
On 07 Feb, 2021
Review #2 received
Received 07 Feb, 2021
Review #1 received
Received 07 Feb, 2021
Reviewer #1 agreed
On 01 Feb, 2021
Editor assigned
On 26 Jan, 2021
Reviewers invited
Invitations sent on 26 Jan, 2021
Submission checks complete
On 26 Jan, 2021
Editor invited
On 26 Jan, 2021
This version was not preprinted
Version 1
Posted 29 Dec, 2020
Published
On 08 Mar, 2021
No community comments so far
Editorial decision: Major Revision
On 11 Jan, 2021
Reviewer #2 agreed
On 10 Jan, 2021
Review #2 received
Received 10 Jan, 2021
Review #1 received
Received 10 Jan, 2021
Reviewer #1 agreed
On 30 Dec, 2020
Reviewers invited
Invitations sent on 29 Dec, 2020
Editor assigned
On 23 Dec, 2020
Submission checks complete
On 23 Dec, 2020
Editor invited
On 23 Dec, 2020
First submitted
On 21 Dec, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Infectious Diseases
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at Malaria Journal.
Background
Malaria 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 facilitated ‘smart surveillance’ followed by required field response within a timeline. The system facilitated data collection of individual case and 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.
Methods
IT system developed for robust malaria surveillance and field response is being continued in the 6th year. Protocol for surveillance control was followed as per the national programme guidilines mentioned earlier. Secondary data from the malaria control system is collated and analysed. Incidence of malaria, active surveillance, malariogenic conditions and its management, malariometric indices, shrinking malaria map were also analysed.
Results
Smart 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 digitizarion (DY) (p<0.001). Early reporting of new cases (within 48 hrs) 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 closure by 14 days. The best impact on reduction in incidence of malaria was recorded in pre-monsoon months (~85%) compared to lower impact in July-August months (~40%).
Conclusion
IT System 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.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
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