OBJECTIVES: Malaria clinical trials need precise endpoints to measure efficacy. In endemic areas where asymptomatic parasitaemia is common, 'fever plus parasitaemia' may not differentiate between malaria cases and non-cases. Case definitions based on parasite cut-off densities may be more appropriate but may vary with age and transmission intensity. This study examines appropriate case definitions from parasitological surveys conducted over a broad range of transmission intensities, using altitude as a proxy for transmission intensity. METHODS: Cross-sectional data collected from 24 villages at different altitudes in an endemic area of northeastern Tanzania were used to calculate malaria-attributable fractions using a modified Poisson regression method. We modelled fever as a function of parasite density and determined the optimum cut-off densities of parasites to cause fever using sensitivity and specificity analyses. RESULTS: The optimum cut-off density varied by altitude in children aged under 5 years: a case definition of 4,000 parasites per mul at altitudes <600 m (high transmission intensity) was most appropriate, compared with 1,000 parasites per mul at altitudes >600 m (low transmission intensity). In children aged over 5 years and adults, there was little variation by altitude and a case definition of any parasites plus fever was the most appropriate. CONCLUSIONS: Locally appropriate case definitions of malaria should be used for research purposes. In our setting, these varied independently with age and transmission intensity.
OBJECTIVES:Malaria clinical trials need precise endpoints to measure efficacy. In endemic areas where asymptomatic parasitaemia is common, 'fever plus parasitaemia' may not differentiate between malaria cases and non-cases. Case definitions based on parasite cut-off densities may be more appropriate but may vary with age and transmission intensity. This study examines appropriate case definitions from parasitological surveys conducted over a broad range of transmission intensities, using altitude as a proxy for transmission intensity. METHODS: Cross-sectional data collected from 24 villages at different altitudes in an endemic area of northeastern Tanzania were used to calculate malaria-attributable fractions using a modified Poisson regression method. We modelled fever as a function of parasite density and determined the optimum cut-off densities of parasites to cause fever using sensitivity and specificity analyses. RESULTS: The optimum cut-off density varied by altitude in children aged under 5 years: a case definition of 4,000 parasites per mul at altitudes <600 m (high transmission intensity) was most appropriate, compared with 1,000 parasites per mul at altitudes >600 m (low transmission intensity). In children aged over 5 years and adults, there was little variation by altitude and a case definition of any parasites plus fever was the most appropriate. CONCLUSIONS: Locally appropriate case definitions of malaria should be used for research purposes. In our setting, these varied independently with age and transmission intensity.
Authors: Melissa A Rolfes; Matthew McCarra; Ng'wena G Magak; Kacey C Ernst; Arlene E Dent; Kim A Lindblade; Chandy C John Journal: Am J Trop Med Hyg Date: 2012-09-17 Impact factor: 2.345
Authors: Thomas Althaus; Yoel Lubell; Venance P Maro; Blandina T Mmbaga; Bingileki Lwezaula; Christine Halleux; Holly M Biggs; Renee L Galloway; Robyn A Stoddard; Jamie L Perniciaro; William L Nicholson; Kelly Doyle; Piero Olliaro; John A Crump; Matthew P Rubach Journal: Trop Med Int Health Date: 2020-01-06 Impact factor: 2.622
Authors: John A Crump; Habib O Ramadhani; Anne B Morrissey; Levina J Msuya; Lan-Yan Yang; Shein-Chung Chow; Susan C Morpeth; Hugh Reyburn; Boniface N Njau; Andrea V Shaw; Helmut C Diefenthal; John A Bartlett; John F Shao; Werner Schimana; Coleen K Cunningham; Grace D Kinabo Journal: Trop Med Int Health Date: 2011-04-07 Impact factor: 2.622
Authors: Bruno P Mmbando; John P Lusingu; Lasse S Vestergaard; Martha M Lemnge; Thor G Theander; Thomas H Scheike Journal: BMC Med Res Methodol Date: 2009-11-12 Impact factor: 4.615
Authors: Behzad Nadjm; Ben Amos; George Mtove; Jan Ostermann; Semkini Chonya; Hannah Wangai; Juma Kimera; Walii Msuya; Frank Mtei; Denise Dekker; Rajabu Malahiyo; Raimos Olomi; John A Crump; Christopher J M Whitty; Hugh Reyburn Journal: BMJ Date: 2010-03-30
Authors: John A Crump; Habib O Ramadhani; Anne B Morrissey; Wilbrod Saganda; Mtumwa S Mwako; Lan-Yan Yang; Shein-Chung Chow; Susan C Morpeth; Hugh Reyburn; Boniface N Njau; Andrea V Shaw; Helmut C Diefenthal; John F Shao; John A Bartlett; Venance P Maro Journal: Clin Infect Dis Date: 2011-02-01 Impact factor: 20.999