World Health Organization, 2021. World Malaria Report 2021. Available at: https://www.who.int/teams/global-malaria-programme/reports/world-malaria-report-2021. Accessed June 28, 2022.
World Health Organization, 2022. WHO Guidelines for Malaria, 3 June 2022. Geneva, Switzerland: WHO.
Kwiatkowski DP, 2005. How malaria has affected the human genome and what human genetics can teach us about malaria. Am J Hum Genet 77: 171–192.
Nortey LN, Anning AS, Nakotey GK, Ussif AM, Opoku YK, Osei SA, Aboagye B, Ghartey-Kwansah G, 2022. Genetics of cerebral malaria: Pathogenesis, biomarkers and emerging therapeutic interventions. Cell Biosci 12: 91.
World Health Organization, 2016. Verbal Autopsy Standards: Ascertaining and Attributing Causes of Death. Geneva, Switzerland: WHO. Available at: https://www.who.int/publications/m/item/verbal-autopsy-standards-the-2016-who-verbal-autopsy-instrument. Accessed October 3, 2024.
World Health Organization, 2022. Verbal Autopsy Standards: The 2022 WHO Verbal Autopsy Instrument. Available at: https://cdn.who.int/media/docs/default-source/classification/other-classifications/autopsy/2022-va-instrument/verbal-autopsy-standards_2022-who-verbal-autopsy-instrument_v1_final.pdf?sfvrsn=c8cf2dda_8. Accessed October 3, 2024.
Byass P, et al., 2012. Strengthening standardized interpretation of verbal autopsy data: The new InterVA-4 tool. Glob Health Action 5: 1–8.
Byass P, et al., 2015. Comparing verbal autopsy cause of death findings as determined by physician coding and probabilistic modelling: A public health analysis of 54 000 deaths in Africa and Asia. J Glob Health 5: 010402.
Tadesse S, 2013. Validating the InterVA model to estimate the burden of mortality from verbal autopsy data: A population-based cross-sectional study. PLoS One 8: e73463.
Dehghan A, Nasirian M, Haghdoost AA, Bahramali E, Sharifi H, 2018. Validation of the verbal autopsy questionnaire for adult deaths in Iran. Med J Islam Repub Iran 32: 7.
Soofi SB, et al., 2015. Diagnostic accuracy of WHO verbal autopsy tool for ascertaining causes of neonatal deaths in the urban setting of Pakistan: A hospital-based prospective study. BMC Pediatr 15: 144.
Ganapathy SS, Yi Yi K, Omar MA, Anuar MFM, Jeevananthan C, Rao C, 2017. Validation of verbal autopsy: Determination of cause of deaths in Malaysia 2013. BMC Public Health 17: 653.
Beiersmann C, Sanou A, Wladarsch E, De Allegri M, Kouyaté B, Müller O, 2007. Malaria in rural Burkina Faso: Local illness concepts, patterns of traditional treatment and influence on health-seeking behaviour. Malar J 6: 106.
Arama C, et al., 2018. Malaria severity: Possible influence of the E670G PCSK9 polymorphism: A preliminary case-control study in Malian children. PLoS One 13: e0192850.
Lyke KE, et al., 2004. Serum levels of the proinflammatory cytokines interleukin-1 beta (IL-1beta), IL-6, IL-8, IL-10, tumor necrosis factor alpha, and IL-12(p70) in Malian children with severe Plasmodium falciparum malaria and matched uncomplicated malaria or healthy controls. Infect Immun 72: 5630–5637.
Malaria Genomic Epidemiology Network, 2019. Insights into malaria susceptibility using genome-wide data on 17,000 individuals from Africa, Asia and Oceania. Nat Commun 10: 5732.
Sim J, Wright CC, 2005. The kappa statistic in reliability studies: Use, interpretation, and sample size requirements. Phys Ther 85: 257–268.
Coulibaly D, et al., 2022. Shifts in the clinical epidemiology of severe malaria after scaling up control strategies in Mali. Front Neurol 13: 988960.
Amek NO, Van Eijk A, Lindblade KA, Hamel M, Bayoh N, Gimnig J, Laserson KF, Slutsker L, Smith T, Vounatsou P, 2018. Infant and child mortality in relation to malaria transmission in KEMRI/CDC HDSS, Western Kenya: Validation of verbal autopsy. Malar J 17: 37.
Herrera S, Enuameh Y, Adjei G, Ae-Ngibise KA, Asante KP, Sankoh O, Owusu-Agyei S, Yé Y, 2017. A systematic review and synthesis of the strengths and limitations of measuring malaria mortality through verbal autopsy. Malar J 16: 421.
Mpimbaza A, Filler S, Katureebe A, Quick L, Chandramohan D, Staedke SG, 2015. Verbal autopsy: Evaluation of methods to certify causes of death in Uganda. PLoS One 10: e0128801.
Watson JA, et al., 2021. Improving statistical power in severe malaria genetic association studies by augmenting phenotypic precision. eLife 10: e69698.
Taylor TE, Fu WJ, Carr RA, Whitten RO, Mueller JS, Fosiko NG, Lewallen S, Liomba NG, Molyneux ME, 2004. Differentiating the pathologies of cerebral malaria by postmortem parasite counts. Nat Med 10: 143–145.
Bujang MA, Adnan TH, 2016. Requirements for minimum sample size for sensitivity and specificity analysis. J Clin Diagn Res 10: YE01–YE06.
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The investigation of factors associated with susceptibility to severe malaria is best achieved using case-control studies. The presence of a history of severe malaria in controls could affect the quality of their phenotype and study findings and hence should be rigorously determined. Here, we assessed the performance of a qualitative questionnaire to identify a history of cerebral malaria in controls in a case-control study of severe malaria in Mali. We evaluated the archived medical records of 220 children diagnosed with severe diseases at health care centers in rural and urban settings in Mali from 2018 to 2019. Parents of enrolled children were then identified and interviewed using a structured questionnaire by an investigator blinded to the diagnosis. The diagnosis derived from the interview was then compared with the diagnosis from the medical records as the reference diagnosis. The sensitivity and specificity of the questionnaire to detect cerebral malaria in history were, respectively, 84% and 76%. The questionnaire was concordant with the medical record diagnosis in 60% (95% CI: 50–71%) of cases. For other clinical phenotypes of malaria (severe malaria anemia, uncomplicated malaria, and severe malaria anemia concurrent with cerebral malaria), sensitivity and specificity ranged from 42% to 85% and 88% to 96%, respectively. Positive and negative predictive values were, respectively, 75% and 85%. The questionnaire demonstrated suitable sensitivity and specificity to identify cerebral malaria in a participant’s history. In sub-Saharan Africa, a region with suboptimal medical record archives, such a tool could be used in case-control studies of severe malaria to select controls.
Financial support: This work was supported by the
Disclosures: The study protocol was evaluated and approved by the ethics committee of the Faculty of Medicine and Pharmacy of Mali prior to the selection of the medical records and the interviews. Individual written informed consent was obtained from each parent before the interview.
Current contact information: Karim Traore, Ali Thera, Drissa Coulibaly, Abdoulaye K. Koné, Boureima Guindo, Bourama Tangara, Aichatou A. Diawara, and Mahamadou A. Thera, Malaria Research and Training Center (MRTC), Faculty of Medicine and Odonto-Stomatology (FMOS), University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali, E-mails: karim@icermali.org, alithera@icermali.org, coulibalyd@icermali.org, fankone@icermali.org, bguindo@icermali.org, bmtangara@icermali.org, aicha215@yahoo.fr, and mthera@icermali.org. Mark A. Travassos, Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD, E-mail: mtravass@som.umaryland.edu.
World Health Organization, 2021. World Malaria Report 2021. Available at: https://www.who.int/teams/global-malaria-programme/reports/world-malaria-report-2021. Accessed June 28, 2022.
World Health Organization, 2022. WHO Guidelines for Malaria, 3 June 2022. Geneva, Switzerland: WHO.
Kwiatkowski DP, 2005. How malaria has affected the human genome and what human genetics can teach us about malaria. Am J Hum Genet 77: 171–192.
Nortey LN, Anning AS, Nakotey GK, Ussif AM, Opoku YK, Osei SA, Aboagye B, Ghartey-Kwansah G, 2022. Genetics of cerebral malaria: Pathogenesis, biomarkers and emerging therapeutic interventions. Cell Biosci 12: 91.
World Health Organization, 2016. Verbal Autopsy Standards: Ascertaining and Attributing Causes of Death. Geneva, Switzerland: WHO. Available at: https://www.who.int/publications/m/item/verbal-autopsy-standards-the-2016-who-verbal-autopsy-instrument. Accessed October 3, 2024.
World Health Organization, 2022. Verbal Autopsy Standards: The 2022 WHO Verbal Autopsy Instrument. Available at: https://cdn.who.int/media/docs/default-source/classification/other-classifications/autopsy/2022-va-instrument/verbal-autopsy-standards_2022-who-verbal-autopsy-instrument_v1_final.pdf?sfvrsn=c8cf2dda_8. Accessed October 3, 2024.
Byass P, et al., 2012. Strengthening standardized interpretation of verbal autopsy data: The new InterVA-4 tool. Glob Health Action 5: 1–8.
Byass P, et al., 2015. Comparing verbal autopsy cause of death findings as determined by physician coding and probabilistic modelling: A public health analysis of 54 000 deaths in Africa and Asia. J Glob Health 5: 010402.
Tadesse S, 2013. Validating the InterVA model to estimate the burden of mortality from verbal autopsy data: A population-based cross-sectional study. PLoS One 8: e73463.
Dehghan A, Nasirian M, Haghdoost AA, Bahramali E, Sharifi H, 2018. Validation of the verbal autopsy questionnaire for adult deaths in Iran. Med J Islam Repub Iran 32: 7.
Soofi SB, et al., 2015. Diagnostic accuracy of WHO verbal autopsy tool for ascertaining causes of neonatal deaths in the urban setting of Pakistan: A hospital-based prospective study. BMC Pediatr 15: 144.
Ganapathy SS, Yi Yi K, Omar MA, Anuar MFM, Jeevananthan C, Rao C, 2017. Validation of verbal autopsy: Determination of cause of deaths in Malaysia 2013. BMC Public Health 17: 653.
Beiersmann C, Sanou A, Wladarsch E, De Allegri M, Kouyaté B, Müller O, 2007. Malaria in rural Burkina Faso: Local illness concepts, patterns of traditional treatment and influence on health-seeking behaviour. Malar J 6: 106.
Arama C, et al., 2018. Malaria severity: Possible influence of the E670G PCSK9 polymorphism: A preliminary case-control study in Malian children. PLoS One 13: e0192850.
Lyke KE, et al., 2004. Serum levels of the proinflammatory cytokines interleukin-1 beta (IL-1beta), IL-6, IL-8, IL-10, tumor necrosis factor alpha, and IL-12(p70) in Malian children with severe Plasmodium falciparum malaria and matched uncomplicated malaria or healthy controls. Infect Immun 72: 5630–5637.
Malaria Genomic Epidemiology Network, 2019. Insights into malaria susceptibility using genome-wide data on 17,000 individuals from Africa, Asia and Oceania. Nat Commun 10: 5732.
Sim J, Wright CC, 2005. The kappa statistic in reliability studies: Use, interpretation, and sample size requirements. Phys Ther 85: 257–268.
Coulibaly D, et al., 2022. Shifts in the clinical epidemiology of severe malaria after scaling up control strategies in Mali. Front Neurol 13: 988960.
Amek NO, Van Eijk A, Lindblade KA, Hamel M, Bayoh N, Gimnig J, Laserson KF, Slutsker L, Smith T, Vounatsou P, 2018. Infant and child mortality in relation to malaria transmission in KEMRI/CDC HDSS, Western Kenya: Validation of verbal autopsy. Malar J 17: 37.
Herrera S, Enuameh Y, Adjei G, Ae-Ngibise KA, Asante KP, Sankoh O, Owusu-Agyei S, Yé Y, 2017. A systematic review and synthesis of the strengths and limitations of measuring malaria mortality through verbal autopsy. Malar J 16: 421.
Mpimbaza A, Filler S, Katureebe A, Quick L, Chandramohan D, Staedke SG, 2015. Verbal autopsy: Evaluation of methods to certify causes of death in Uganda. PLoS One 10: e0128801.
Watson JA, et al., 2021. Improving statistical power in severe malaria genetic association studies by augmenting phenotypic precision. eLife 10: e69698.
Taylor TE, Fu WJ, Carr RA, Whitten RO, Mueller JS, Fosiko NG, Lewallen S, Liomba NG, Molyneux ME, 2004. Differentiating the pathologies of cerebral malaria by postmortem parasite counts. Nat Med 10: 143–145.
Bujang MA, Adnan TH, 2016. Requirements for minimum sample size for sensitivity and specificity analysis. J Clin Diagn Res 10: YE01–YE06.
Past two years | Past Year | Past 30 Days | |
---|---|---|---|
Abstract Views | 292 | 292 | 77 |
Full Text Views | 20 | 20 | 5 |
PDF Downloads | 26 | 26 | 7 |