Back

Estimating malaria attributable fraction using quantitative PCR in a longitudinal cohort in Eastern Uganda

Martin, A.; Wang, Q.; Babirye, S.; Arinaitwe, E.; Zedi, M.; Ssewanyana, I.; Namirimu, F. N.; Nayebare, P.; Olwoch, P.; Tukwasibwe, S.; Jagannathan, P.; Nankabirwa, J. I.; Kamya, M.; Dorsey, G.; Greenhouse, B.; Briggs, J.; Rodriguez-Barraquer, I.

2026-02-27 infectious diseases
10.64898/2026.02.24.26347052 medRxiv
Show abstract

Persistent, asymptomatic Plasmodium infections are common in areas of high transmission due to acquired immunity. When asymptomatically infected individuals seek care for a fever caused by something other than malaria parasites, they may test positive for parasites and be incorrectly diagnosed as having clinical malaria. This study used distributions of qPCR parasite densities to estimate the fraction of fever attributable to malaria (malaria attributable fraction, MAF) in a cohort of 659 individuals followed for up to 3 years from three geographically distinct zones in eastern Uganda. Prevalence of P. falciparum by qPCR ranged from 47-63% in the three zones, with over 95% of cohort members parasitemic at least once. Overall MAF across the three zones ranged from 54-64%. MAF was highest in under-five year-olds (72%), next highest in 5-15 year-olds (56%) and lowest in adults over 16 (45%). Notably, nearly 50% of fevers with low to moderate parasite density (10 - 100 parasite/ microliter) were attributed to malaria. MAF-corrected incidence was higher than the definition of clinical malaria used in many vaccine field-studies (fever and parasite density [≥] 5000/microliter) and the difference varied by age group: MAF-corrected incidence was 18% higher in children under five, 7% higher in 5-15 year olds, and 70% higher in adults. These results suggest parasite density thresholds commonly used to define primary study outcomes will underestimate the true incidence of clinical malaria. Studies aiming to precisely estimate intervention effects on incidence should consider estimating MAF in their study population and incorporating it into their design.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
The American Journal of Tropical Medicine and Hygiene
60 papers in training set
Top 0.1%
22.5%
2
Malaria Journal
48 papers in training set
Top 0.2%
14.4%
3
PLOS Global Public Health
293 papers in training set
Top 0.8%
10.4%
4
The Journal of Infectious Diseases
182 papers in training set
Top 0.3%
8.4%
50% of probability mass above
5
Scientific Reports
3102 papers in training set
Top 31%
4.0%
6
PLOS ONE
4510 papers in training set
Top 39%
3.6%
7
BMC Infectious Diseases
118 papers in training set
Top 1%
3.6%
8
BMJ Global Health
98 papers in training set
Top 1%
2.7%
9
BMC Medicine
163 papers in training set
Top 3%
1.9%
10
Clinical Infectious Diseases
231 papers in training set
Top 2%
1.9%
11
The Lancet Microbe
43 papers in training set
Top 0.5%
1.8%
12
Transactions of The Royal Society of Tropical Medicine and Hygiene
16 papers in training set
Top 0.2%
1.7%
13
Emerging Infectious Diseases
103 papers in training set
Top 1%
1.7%
14
BMJ Open
554 papers in training set
Top 9%
1.7%
15
PLOS Neglected Tropical Diseases
378 papers in training set
Top 3%
1.7%
16
International Journal of Infectious Diseases
126 papers in training set
Top 2%
1.7%
17
Open Forum Infectious Diseases
134 papers in training set
Top 1%
1.5%
18
The Lancet Infectious Diseases
71 papers in training set
Top 2%
1.3%
19
PLOS Medicine
98 papers in training set
Top 3%
1.2%
20
Tropical Medicine & International Health
15 papers in training set
Top 0.5%
0.9%
21
eLife
5422 papers in training set
Top 58%
0.7%
22
Infectious Disease Modelling
50 papers in training set
Top 1%
0.6%