B Shantharam Baliga1, Shrikala Baliga1,2, Animesh Jain1,2, Naveen Kulal3, Manu Kumar4, Naren Koduvattat5, B G Prakash Kumar6, Arun Kumar7, Susanta K Ghosh8,9. 1. Kasturba Medical College Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, India. 2. Manipal Center for Infectious Diseases, Prasanna School of Public Health, Manipal Academy of Higher Education, Manipal, Karnataka, India. 3. Department of Public Health, Dakshina Kannada District, Mangalore, Karnataka, 575001, India. 4. Officer On Special Duty, Chief Minister's Secretariat Bengaluru, Bangalore, Karnataka, 560001, India. 5. I-Point Consulting, Punja Arcade, Lalbagh, Mangalore, Karnataka, 575003, India. 6. Directorate of Health and Family Welfare Services, Government of Karnataka, Bangalore, Karnataka, 560009, India. 7. General Hospital, Shikaripura, Karnataka, 577427, India. 8. ICMR-National Institute of Malaria Research (Field Unit), Nirmal Bhawan, ICMR Campus, Poojanahalli, Kannamangla Post, Devanahalli Taluk, Bangalore, Karnataka, 562110, India. ghoshnimr@gmail.com. 9. Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India. ghoshnimr@gmail.com.
Abstract
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 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. METHODS: IT 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. 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 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%). CONCLUSION: MCS 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.
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 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. METHODS: IT 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. 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 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%). CONCLUSION:MCS helped to micromanage control activities, such as robust reporting, incidence-centric active surveillance, early and complete treatment, documentation of full treatment of each malariapatient, 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.
Authors: Konrad Siegert; Welmoed van Loon; Prabhanjan P Gai; Jessica L Rohmann; Marco Piccininni; Anatol-Fiete Näher; Archith Boloor; Damodara Shenoy; Chakrapani Mahabala; Suyamindra S Kulkarni; Arun Kumar; Jacob Wedam; Pramod Gai; Rajeshwari Devi; Animesh Jain; Tobias Kurth; Frank P Mockenhaupt Journal: Int J Environ Res Public Health Date: 2021-11-12 Impact factor: 3.390