Seasonality and malaria in a west African village: does high parasite density predict fever incidence?

Am J Epidemiol. 1997 May 1;145(9):850-7. doi: 10.1093/oxfordjournals.aje.a009179.

Abstract

In this cohort study, the authors studied the effect of blood malaria parasite density on fever incidence in children in an endemic area with 9 days' follow-up of 1- to 12-year-old children during two time periods: the end of the dry season (May 1993: n = 783) and the end of the rainy season (October 1993: n = 841) in Bougoula, West Africa (region of Sikasso, Mali). The cumulative incidence of fever (temperature > 38.0 degrees C) was 2.0% in the dry season and 8.2% in the rainy season (p < 0.0001). In the rainy season, the risk of fever was increased in children of ages 1-3 years (relative risk (RR) = 2.5, 95% confidence interval (CI) 1.6-4.1); in those with an initial parasitemia > 15,000/microliter (RR = 2.7, 95% CI 1.4-5.4); in children with an enlarged spleen (RR = 2.0, 95% CI 1.2-3.3); or in those with anemia (hematocrit < 30%: RR = 1.8, 95% CI 1.1-2.9). In the dry season, anemia was the only predictor of fever incidence. In the rainy season, the best predictors of fever were, in order, age (< 4 years), enlarged spleen, and high parasite density. Even in the higher risk groups, the cumulative incidence was < 20%. The authors conclude that most children with high parasite density do not develop fever subsequently. The association between parasite density and fever varies according to age and season. Since even high levels of parasite density do not reliably predict fever incidence, parasite density should be considered as just one of a group of indicators that increase the probability of a fever of malarial origin.

PIP: In a cohort study, the effect of blood malaria parasite density on fever incidence in children was studied in an endemic area with 9 days' follow-up of children aged 1-12 years during two time periods: the end of the dry season (May 1993: n = 783) and the end of the rainy season (October 1993: n = 841) in Bougoula, West Africa (region of Sikasso, Mali). The number of registered children was 928 in the dry season and 998 in the rainy season. Complete follow-up and information were available for 835 children in the dry season and for 964 children in the rainy season. The 9-day cumulative fever incidence (body temperature above 38.0 degrees Celsius) increased from 2.0% in the dry season to 8.2% in the rainy season (p 0.0001). In the rainy season, the risk of fever increased in children aged 1-3 years (relative risk [RR] = 2.5; 95% confidence interval [CI], 1.6-4.1); in those with an initial parasitemia greater than 15,000/mcl (RR = 2.7; 95% CI, 1.4-5.4); in those with an enlarged spleen (RR = 2.0; 95% CI, 1.2-3.3); or in those with anemia (hematocrit 30%: RR = 1.8; 95% CI, 1.1-2.9). In the dry season, anemia (hematocrit 30%) was the only predictor of fever incidence with a cumulative incidence of 10.0%. In nonanemic children, a parasite count of 2000/mcl was the next best predictor. In the rainy season, the best predictors of fever were age (4 years), enlarged spleen, and high parasite density (1/mcl). Even in the higher risk groups, the cumulative incidence was 20%. Most children with high parasite density do not develop fever subsequently. The association between parasite density and fever varies according to age and season. Since even high levels of parasite density do not reliably predict fever incidence, parasite density should be considered not so much a direct marker of an ongoing attack but as just one indicator of the likelihood of a current or imminent attack or even one just passed.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Africa, Western / epidemiology
  • Animals
  • Anopheles / growth & development
  • Child
  • Child, Preschool
  • Cohort Studies
  • Female
  • Fever / epidemiology
  • Humans
  • Incidence
  • Infant
  • Logistic Models
  • Malaria / epidemiology*
  • Male
  • Multivariate Analysis
  • Parasitemia / epidemiology
  • Plasmodium falciparum / growth & development
  • Proportional Hazards Models
  • Regression Analysis
  • Seasons*
  • Statistics, Nonparametric