• Adapting Reactive Case Detection Strategies for falciparum Malaria in a Low-Transmission Area in Cambodia.

      Rossi, G; Van den Bergh, R; Nguon, C; Debackere, M; Vernaeve, L; Khim, N; Kim, S; Menard, D; De Smet, M; Kindermans, JM (Oxford University Press, 2018-01-06)
      Reactive case detection around falciparum malaria cases in Cambodia presents a low output. We improved it by including individuals occupationally coexposed with index case patients and using polymerase chain reaction-based diagnosis. The positivity rate increased from 0.16% to 3.9%.
    • 'I could not join because I had to work for pay.': A qualitative evaluation of falciparum malaria pro-active case detection in three rural Cambodian villages

      Taffon, P; Rossi, G; Kindermans, JM; Van den Bergh, R; Nguon, C; Debackere, M; Vernaeve, L; De Smet, M; Venables, E (Public Library of Science, 2018-04-12)
      Pro-active case detection (Pro-ACD), in the form of voluntary screening and treatment (VSAT) following community mobilisation about 'asymptomatic malaria', is currently being evaluated as a tool for Plasmodium falciparum elimination in Preah Vihear Province, Cambodia.
    • Identifying exceptional malaria occurrences in the absence of historical data in South Sudan: a method validation

      Benedetti, G; White, RA; Akello Pasquale, H; Stassjins, J; van den Boogaard, W; Owiti, P; Van den Bergh, R (International Union Against Tuberculosis and Lung Disease, 2019-09-21)
      Background: Detecting unusual malaria events that may require an operational intervention is challenging, especially in endemic contexts with continuous transmission such as South Sudan. Médecins Sans Frontières (MSF) utilises the classic average plus standard deviation (AV+SD) method for malaria surveillance. This and other available approaches, however, rely on antecedent data, which are often missing. Objective: To investigate whether a method using linear regression (LR) over only 8 weeks of retrospective data could be an alternative to AV+SD. Design: In the absence of complete historical malaria data from South Sudan, data from weekly influenza reports from 19 Norwegian counties (2006–2015) were used as a testing data set to compare the performance of the LR and the AV+SD methods. The moving epidemic method was used as the gold standard. Subsequently, the LR method was applied in a case study on malaria occurrence in MSF facilities in South Sudan (2010–2016) to identify malaria events that required a MSF response. Results: For the Norwegian influenza data, LR and AV+SD methods did not perform differently (P  0.05). For the South Sudanese malaria data, the LR method identified historical periods when an operational response was mounted. Conclusion: The LR method seems a plausible alternative to the AV+SD method in situations where retrospective data are missing.