• View in gallery
    Figure 1.

    Consort flow diagram of participants in malaria surveillance. MAF = malaria-attributable fraction of fevers; PPV = positive predictive value; RDT = rapid diagnostic test.

  • View in gallery
    Figure 2.

    Malaria test positivity rates (TPRs) in three sites in Malawi. This figure appears in color at www.ajtmh.org.

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Overdiagnosis of Malaria Illness in an Endemic Setting: A Facility-Based Surveillance Study in Malawi

Ingrid PetersonCenter for Vaccine Development and Global Health, University of Maryland Baltimore, Baltimore, Maryland;
Blantyre Malaria Project, College of Medicine, University of Malawi, Blantyre, Malawi;

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Atupele Kapito-TemboMalaria Alert Center, College of Medicine, University of Malawi, Blantyre, Malawi;

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Andrew BauleniMalaria Alert Center, College of Medicine, University of Malawi, Blantyre, Malawi;

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Osward NyirendaBlantyre Malaria Project, College of Medicine, University of Malawi, Blantyre, Malawi;

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Paul PensuloBlantyre Malaria Project, College of Medicine, University of Malawi, Blantyre, Malawi;

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William StillCenter for Vaccine Development and Global Health, University of Maryland Baltimore, Baltimore, Maryland;

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Clarissa ValimDepartment of Global Health, Boston University School of Public Health, Boston, Massachusetts;

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Lauren CoheeCenter for Vaccine Development and Global Health, University of Maryland Baltimore, Baltimore, Maryland;

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Terrie TaylorDepartment of Osteopathic Medical Specialties, College of Osteopathic Medicine, Michigan State University, East Lansing, Michigan

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Don P. MathangaMalaria Alert Center, College of Medicine, University of Malawi, Blantyre, Malawi;

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Miriam K. LauferCenter for Vaccine Development and Global Health, University of Maryland Baltimore, Baltimore, Maryland;

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Abstract.

In endemic settings where asymptomatic malaria infections are common, malaria infection can complicate fever diagnosis. Factors influencing fever misdiagnosis, including accuracy of malaria rapid diagnostic tests (mRDTs) and the malaria-attributable fraction of fevers (MAF), require further investigation. We conducted facility-based surveillance in Malawi, from January 2012 through December 2013 in settings of high perennial (Chikhwawa), high seasonal (Thoylo), and moderate seasonal (Ndirande) malaria transmission. Consecutive patients presenting to outpatient departments were screened; those with suspected malaria illness were tested by mRDT or routine thick-smear microscopy. Test positivity rates (TPRs), positive predictive value (PPVs) of mRDTs, and MAFs were calculated by site, age, and season. Of 41,471 patients, 10,052 (24.2%) tested positive for malaria. The TPR was significantly greater in Chikhwawa (29.9%; 95% CI, 28.6–30.0) compared with Thyolo (13.2%; 95% CI, 12.5–13.7) and Ndirande (13.1%; 95% CI, 12.2–14.4). The overall PPV was 77.8% (95% CI, 76.8–78.7); it was lowest among infants (69.9%; 95% CI, 65.5–74.2) and highest among school-age children (81.9%; 95% CI, 80.3–83.4). Malaria infection accounted for about 50% of fevers in children younger than 5 years old with microscopy-confirmed Plasmodium falciparum infection, and less than 20% of such fevers in school-age children. Outpatient settings in Malawi had a high burden of malaria illness, but also possible overdiagnosis of malaria illness. Interventions to reduce malaria transmission and rapid testing for other common febrile illness may improve diagnostic clarity among outpatients in malaria endemic settings.

BACKGROUND

In malaria-endemic settings, inaccurate diagnosis of malaria illness can complicate clinical management of fevers. Malaria illness frequently presents with non-specific symptoms that overlap with those of other common viral and bacterial illnesses.1 In settings of high transmission where asymptomatic malaria infection is common, presence of fever frequently triggers malaria testing, but the fever may be the result of non-malaria infections even when malaria parasites are present.2 Although malaria rapid diagnostic tests (mRDTs) are an objective criterion for malaria diagnosis, they can produce false-positive results by indicating malaria infection in patients who are not infected; this is particularly common in individuals who have recently recovered from malaria illness.35 False-negative mRDT results in individuals with low levels of parasitemia also complicate identification of illness etiology in febrile individuals.6

Accuracy of mRDTs7 and the likelihood that malaria is the underlying cause of fever in patients with Plasmodium falciparum infection vary widely across settings.2 Positive results from histidine-rich protein 2 (HRP-2)-based mRDTs in individuals who are not infected with malaria can arise from persistent HRP-2 antigenemia after antimalarial treatment and parasite clearance. This may be common in areas with high rates of antimalarial self-treatment prior to clinic attendance, particularly in young children with little acquired immunity to malaria and consequently slower clearance of the HRP-2 antigen.8 Acquired immunity to malaria after repeated infection limits malaria symptoms, particularly fever,9 and reduces the likelihood that malaria illness is the underlying cause of fever in patients with P. falciparum infection. In high-transmission settings in Africa, a large proportion of apparently well, afebrile children are infected with malaria parasites,1012 and fevers in children with parasites may often be attributed incorrectly to malaria illness.2

An important metric for assessing the potential overdiagnosis of malaria illness is the malaria-attributable fraction of fevers (MAF), which estimates the proportion of febrile patients with P. falciparum infection in which P. falciparum is the underlying cause of fever.13 The MAF assumes that the background rate of non-malaria febrile illness is the same in children with and without malaria infection, and that any additional burden of fever in malaria-positive patients is attributable to P. falciparum infection. Primarily focusing on young children, studies estimating the MAF have been conducted in a wide range of transmission settings, including settings of moderate and low transmission.2,8,1420 However, detailed analyses are lacking regarding the influence of age and malaria transmission setting on the potential for overdiagnosis of malaria illness. To assess the overdiagnosis of malaria among febrile outpatients in Malawi, we estimated MAFs and the positive predictive value (PPV) of mRDTs using surveillance data from diverse malaria transmission settings: high perennial transmission, high seasonal transmission, and moderate seasonal transmission.

METHODS

Study site.

This facility-based surveillance study was conducted in the southern region of Malawi, from January 2012 through December 2013, in the outpatient departments of two rural district hospitals (one in Chikhwawa District and one in Thyolo District), and an urban health center in Ndirande township, Blantyre. Chikhwawa District is located in the lower Shire Valley at an altitude of 500 feet above sea level; the district has high malaria transmission, with an estimated entomological inoculation rate (EIR) for P. falciparum of 183 bites/year.21 Thyolo District is 3,000 feet above sea level and has a poorly characterized malaria burden. Ndirande township is a high-density settlement situated 3,400 feet above sea level within Malawi’s commercial capital of Blantyre. In Ndirande, malaria transmission is low (estimated EIR, < 1), with recent travel being a strong risk factor for clinical malaria.22 The district hospitals of Chikhwawa and Thyolo are the only government hospitals in their areas; the Ndirande clinic is the primary source of government outpatient services for township residents. All outpatient services at these facilities were provided free of charge, in accordance with Malawi Ministry of Health policy. Malawi’s malaria burden remained stable from 2012 to 2018.23,24

Passive surveillance.

Our study design has been described previously.25 Briefly, surveillance was conducted 1 week/month, for a total of 12 weeks/year at each site. During the week, consecutive patients of all ages who presented to outpatient departments were screened. Data on visit date, study site, gender, age, axillary temperature, reported complaint of fever, and diagnostic test results were recorded for all patients with an acute illness, and were transcribed by study staff from the patient’s health passport into an electronic data capture system at the time of discharge. Malaria testing by mRDT was conducted based on clinical suspicion at the discretion of the facility clinician using either SD BIOLINE malaria Ag Pf (Standard. Diagnostics, Inc., Alere) or Paracheck malaria Ag Pf (Orchid Biomedical Systems, Goa, India). These mRDTs test for the presence of HRP-2 and have similar levels of accuracy.26,27 If mRDTs were unavailable or the clinician requested a blood smear, thick microscopy slides were obtained and read by facility laboratory staff. Slides were stained with Fields’s stain and read by trained facility staff who recorded semi-quantitative results. In patients with a positive mRDT, a confirmatory blood smear was processed in our research laboratory. Confirmatory microscopy was conducted in our research laboratory by two trained microscopists; a tie-breaker evaluation was conducted in the case of discrepant results. These microscopy results were not available in real time and did not influence the clinical diagnosis.

Data analysis.

A positive malaria diagnostic test was defined as either a positive mRDT or a positive blood smear obtained in the health facility. Patients usually received a single malaria test (either mRDT or blood smear) in the health facility; patients tested by both methods represent less than 1% of the sample and were excluded from analysis because they may have had unusual clinical presentations. Fever was assessed on the day of the outpatient visit by a facility nurse and was defined as either an axillary temperature above 37.5°C or self-reported fever documented in the health passport. Age was based on report of the patient or guardian and was stratified as follows: infants younger than 1 year; young children, 1 to 5 years old; school-age children, 6 to 15 years old; and adults, more than 15 years old. Season was defined as rainy (December–March) or dry (April–November).

The test positivity rate (TPR) was calculated as the number of positive malaria tests divided by the number of people tested. Within each site and season, TPRs were smoothed over age in years, using a centered, weighted moving average based on three data points. Routine thick-smear microscopy was conducted for malaria diagnosis in 4,897 recruited patients (Figure 1); MAFs were estimated by site, season, and age group using data from this subset of 4,897 patients. We used a method described previously13 to develop strata-specific logistic models to obtain odds ratios (OR) for fever associated with positive microscopy; infants and children 1 to 5 years old were combined into a single age group to reduce data sparsity. MAFs were calculated as: OR – 1/OR. We also developed logistic models to estimate MAFs associated with each semi-quantitative measure of parasite density compared with no parasites seen on microscopy. We interpreted MAFs as the proportion of fevers resulting from malaria illness among all febrile outpatients with a positive malaria smear. When the odds of fever were greater in patients without a positive microscopy test compared with a positive microscopy test, we assigned a value of zero to the MAF and interpreted it as indicating that a negligible proportion of fevers in microscopy-positive patients were attributable to malaria illness. The population malaria-attributable fraction (PMAF) was calculated as the parasitemia prevalence multiplied by the MAF and was interpreted as the proportion of all outpatient fevers attributable to malaria illness. MAFs and PMAFs characterize malaria-attributable fevers on a population level, but they cannot be used to infer cause of fever in individual patients.

Figure 1.
Figure 1.

Consort flow diagram of participants in malaria surveillance. MAF = malaria-attributable fraction of fevers; PPV = positive predictive value; RDT = rapid diagnostic test.

Citation: The American Journal of Tropical Medicine and Hygiene 104, 6; 10.4269/ajtmh.20-1209

We evaluated the PPV of mRDTs compared with confirmatory thick-smear microscopy conducted in our research laboratory. Within strata of site, season, age group, and fever status, PPVs were calculated as the proportion of microscopy-positive slides among all slides in patients with a positive mRDT result. The normal approximation of a binomial probability was used to calculate 95% CIs around estimates of TPRs and PPVs.28 All statistical analyses were conducted using SAS statistical software (v. 9.3; SAS Institute, Cary, NC).

RESULTS

From January 2012 through December 2013, we screened 50,482 outpatients across the three sites, of whom 41,471 (82.2%) were tested for malaria (Table 1). A greater proportion of outpatients received a malaria test in Chikhwawa (89.8%) compared with Thyolo (78.9%) and Ndirande (74.7%). The proportion of patients tested was similar during the rainy season (83.9%) compared with the dry season (80.8%)— a trend observed at all sites. Malaria testing was conducted more frequently in young children (86.1%) and school-age children (85.6%), compared with infants (80.1%) and adults (78.4%). Malaria testing was also more frequent among febrile patients (92.7%) compared with non-febrile patients (73.2%). Among patients tested for malaria, 4,897 (11.8%) were tested by microscopy alone; 36,474 (88.2%) were tested by mRDT alone.

Table 1

Characteristics of patients attending outpatient clinics in three sites in Malawi, 2011 to 2012

CharacteristicTotal, N (%)Chikhwawa, N (%)Thyolo, N (%)Ndirande, N (%)P value*
Total50,482 (100)20,282 (40.2)15,938 (31.6)14,262 (28.3)
Gender
 Male21,052 (41.7)8,144 (40.1)6,528 (41.0)6,380 (44.7)
 Female29,430 (58.3)12,138 (59.9)9,410 (59.0)7,882 (55.3)< 0.001
Age, y
 > 15,621 (11.1)1,849 (9.1)2,103 (13.2)1,669 (11.7)
 1–514,570 (28.9)5,630 (27.8)4,933 (30.9)4,007 (28.1)
 6–159,299 (18.4)4,147 (20.5)2,423 (15.2)2,729 (19.1)
 > 1520,992 (41.6)8,656 (42.7)6,479 (40.7)5,857 (41.1)< 0.001
Season
 Rainy (Dec.–Mar.)22,209 (43.9)9,089 (44.8)7,400 (46.4)5,720 (40.1)
 Dry (Apr.–Nov.)28,273 (56.1)11,193(55.2)8,538 (53.6)8,542 (59.9)<0.001
Fever
 Present27,667 (54.8)10,936 (53.9)8,512 (53.4)8,219 (57.6)
 Absent22,800 (45.2)9,341 (46.1)7,419 (46.6)6,040 (42.4)< 0.001
Received malaria test
 Yes41,471 (82.2)18,222 (89.8)12,590 (78.9)10,659 (74.7)
 No9,011 (17.9)2,060 (10.2)3,348 (21.0)3,603 (25.3)< 0.001
Malaria test result
 Positive10,019 (24.2)6,403 (35.2)1,973 (15.8)1,643 (15.4)
 Negative31,346 (75.8)11,784 (64.8)10,557 (84.2)9,005 (84.6)< 0.001

Chi-squared P value of difference by site.

Self-reported or measured; 15 subjects were missing data on fever status.

Excludes 106 patients tested by both malaria rapid diagnostic tests and microscopy.

Malaria TPRs.

Among patients tested for malaria, 10,052 (24.2%) were positive (Table 1), including 9,035 (24.8%) patients tested by mRDT and 984 (20.1%) patients tested by routine microscopy. The TPR was significantly greater in Chikhwawa (29.9%; 95% CI, 28.6–30.0) compared with Thyolo (13.2%; 95% CI, 12.5–13.7) and Ndirande (13.1%; 95% CI, 12.2–14.4). Chikhwawa had the greatest TPR across all seasons and age groups. At all sites, the TPR rose from infancy to a peak in school-age children, then declined in adults. The peak was attained at about 5 years of age in Chikhwawa and at around 10 years of age in Ndirande and Thyolo. TPRs were lower in the dry season compared with the rainy season through 20 years of age in Thyolo, but varied only modestly across seasons in Chikhwawa and Ndirande (Figure 2).

Figure 2.
Figure 2.

Malaria test positivity rates (TPRs) in three sites in Malawi. This figure appears in color at www.ajtmh.org.

Citation: The American Journal of Tropical Medicine and Hygiene 104, 6; 10.4269/ajtmh.20-1209

Positive predictive value of mRDTs.

Among 9,035 patients with a positive mRDT, 7,202 (79.4%) had a confirmatory microscopy result and were included in the PPV analysis (Table 2). The overall PPV of mRDTs in study participants was 77.8% (95% CI, 76.8–78.7); PPVs were similar across study sites, ranging from 77.1% in Chikhwawa to 80.5% in Ndirande. PPVs varied significantly by age group (P value < 0.0001); the PPV was lowest among infants (69.9%) and highest among school-age children (81.9%). Among all children younger than 5 years old, the PPV was 74.2%; it was 79.0% among children 5 years old or older and adults. In the rural settings of Chikhwawa and Thyolo, PPVs were significantly greater during the rainy season compared with the dry season (P = 0.0246). Conversely, in Ndirande, the PPV was greater during the dry season (87.2%) compared with the rainy season (77.2%, P < 0.0001). At all sites, PPVs were significantly greater in patients with fever compared with patients without fever.

Table 2

Positive predictive value of malaria rapid diagnostic test by site, age, season, and presence of fever

CharacteristicN (%)*Positive predictive value (95% CI)
All sitesChikhwawaThyoloNdirande
Total7,202 (100.0)77.8 (76.8–78.7)77.1 (75.9–78.3)78.2 (76.2–80.2)80.5 (78.1–82.9)
Age group
 < 1 y414 (5.8)69.9 (65.5–74.2)71.6 (66.5–76.8)64.9 (54.0–75.7)67.3 (54.9–79.7)
 1–5 y2,334 (32.4)75.6 (73.9–77.3)74.7 (72.6–76.9)77.0 (73.3–80.7)77.9 (73.1–82.6)
 6–15 y2,278 (31.6)81.9 (80.3–83.4)80.6 (78.6–82.7)82.5 (79.2–85.8)86.6 (82.8–90.4)
 > 15 y2,176 (30.2)77.4 (75.6–79.1)77.0 (74.7–79.3)77.0 (73.3–80.6)79.3 (75.3–83.4)
 < 5 y2,395 (33.3)74.2 (72.5–76.0)73.7 (71.5–75.8)75.8 (72.0–79.7)74.7 (69.7–79.6)
 ≥ 5 y4,807 (66.7)79.8 (78.7–81.0)79.0 (77.6–80.5)79.9 (77.5–82.4)82.8 (80.1–85.5)
Season
 Rainy4,194 (41.8)78.9 (77.7–80.0)78.9 (77.4–80.4)79.6 (77.4–81.8)77.2 (74.1–80.3)
 Dry3,008 (58.2)75.6 (73.9–77.3)73.9 (71.9–76.0)71.9 (66.8–77.0)87.2 (83.7–90.7)
Any fever
 Presence4,397 (61.2)81.5 (80.1–83.0)80.1 (78.2–81.9)82.8 (79.7–86.0)86.7 (83.2–90.2)
 Absence2,791 (38.8)75.1 (73.7–76.5)75.5 (73.8–77.2)74.8 (71.6–77.9)73.8 (69.7–77.8)

Sample size for analysis.

Malaria-attributable fraction of fevers.

Among patients with P. falciparum infection detected by microscopy, malaria illness accounted for about 20% to 50% of fevers in various age groups, with differences by site and season. Combining all sites, MAFs were 56.5% (95% CI, 41.6–67.6) in patients 0 to 5 years old, 18.3% (95% CI, 0.0–39.1) in school-age patients, and 22.4% (95% CI, 0.1–39.8) in adult patients (Table 3). In the high perennial-transmission setting of Chikhwawa, patients 0 to 5 years old had sizeable MAFs year-round, reaching 82% during the rainy season. Among school-age patients in Chikhwawa, MAFs were moderate during the rainy season (26.3%); however, during the dry season, school-age patients with parasitemia had lower odds of fever than those without parasitemia (MAF = 0). MAFs in adult patients in Chikhwawa were low to moderate (15.4–31.0%) year-round. A similar age-related pattern was observed in the high seasonal-transmission setting of Thyolo, albeit with differences in seasonality. In Thyolo, MAFs were more than 60% year-round in patients 0 to 5 years old, substantial in school-age patients only during the dry season (68.1%), and low (7.7–15.6%) year-round in adult patients. In urban Ndirande, MAFs were greatest during the dry season in patients of all ages and, overall, of a similar magnitude among school-age patients (27.9%) and patients 0 to 5 years old (31.7%). In addition to trends by age, site, and season, we observed that MAFs increased across higher categories of parasite density in patients 0 to 5 years old, but not in other age groups (Supplemental Table 1).

Table 3

Malaria-attributable fraction of fevers in outpatients in Malawi by age, site. and season

SeasonAge group
0–5 y6–15 y> 15 y
NParasite prevalence (%)*MAF, % (95% CI)PAF (%)NParasite prevalence (%)MAF, % (95% CI)PAF (%)NParasite prevalence (%)MAF, % (95% CI)PAF (%)
All sites
 Total1,86523.756.5 (41.6–67.6)13.41,09526.519.6 (0.0–39.1)5.2203713.922.4 (0.1–39.8)3.1
 Rainy58426.578.4 (48.9–90.8)20.835835.20.0 (0.0–36.5)0.063915.921.1 (0.0–48.7)3.4
 Dry1,31722.623.6 (30.2–44.2)5.373722.325.7 (0.0–49.1)5.7139812.923.6 (0.0–44.2)3.3
Chikhwawa (rural, high transmission)
 Total57543.857.7 (29.6–74.6)25.336640.70.0 (0.0–31.5)0.056419.216.8 (0.0–47.0)3.2
 Rainy22350.782.0 (15.8–96.1)41.616953.326.3 (0.0–61.0)14.025123.515.4 (0.0–57.7)3.6
 Dry35239.544.9 (3.6–68.5)17.719729.90.0 (0.0–32.6)0.031315.731.0 (0.0–62.9)4.9
Thyolo (rural, seasonal transmission)
 Total30314.564.7 (6.8–86.6)2.110624.539.9 (0.0–76.6)6.030210.935.9 (0.0–68.4)1.2
 Rainy14513.763.2 (0.0–91.9)1.94729.80.0 (0.0–65.9)8.911915.653.5 (0.0–82.8)2.4
 Dry15815.266.4 (0.0–90.5)2.35920.368.1 (0.0–92.3)4.11837.70.0 (0.0–60.0)0.6
Ndirande (urban, low transmission)
 Total98714.831.7 (0.0–54.9)2.262318.527.9 (23.4–31.5)3.4117112.133.4 (5.2–53.2)1.5
 Rainy1806.70.0 (0.0–79.2)0.414215.523.4 (0.0–76.1)2.42698.973.9 (0.0–90.6)0.8
 Dry80716.636.9 (7.0–60.8)2.848119.331.5 (0.0–58.1)3.790213.123.8 (0.0–48.3)1.7

MAF = malaria-attributable fraction of fevers; PAF = population-attributable fraction.

Percentage of malaria slides with parasites detected.

The MAF was calculated as (OR – 1)/OR, where OR is the odds ratio of fever given a positive malaria slide. MAF was set to zero if odds of fever were higher in patients without a positive malaria slide compared with patients with a positive malaria slide

PAF calculated as MAF × parasite prevalence.

Estimates of the PMAF, the proportion of fevers attributable to malaria in the total outpatient population, were less than 5% in most age groups and seasons (Table 3). This suggests that, at study facilities, most outpatient fevers were caused by non-malaria illnesses. However, malaria did account for a sizeable proportion of all outpatient fevers among young children in Chikhwawa during the rainy (41.6%) and dry (17.7%) seasons, and a moderate proportion of all outpatient fevers in school-age children during the rainy season in Chikhwawa (14.0%) and Thyolo (8.9%).

Malaria diagnosis and treatment.

In total, 87.9% of patients with a positive malaria test (by either mRDT or routine microscopy) were diagnosed with malaria illness. Among test-positive patients, diagnosis of malaria was slightly more common among those with fever (89.6%; 95% CI, 88.9–to 90.4) compared with those without fever (84.9%; 95% CI, 83.7–86.1; P < 0.0001), and was less common during the rainy season (85.3%; 95% CI, 84.4–86.2) compared with the dry season (91.3%; 95% CI, 90.5–92.1; P < 0.0001). Across the study sites, an artemisinin-based antimalarial medication was prescribed in 98.8% of test-positive patients.

DISCUSSION

In this large facility-based surveillance study, we evaluated trends in the outpatient malaria burden by age, season, and transmission setting in Malawi and found that malaria TPRs were moderate to high in all age groups and seasons. High rates of malaria testing and antimalarial prescribing highlight malaria’s primacy in these clinical settings. Across the facilities, 75% to 90% of outpatients with symptoms of infection were tested for malaria, and 98.8% of test-positive patients were prescribed an antimalarial medication. Accuracy of mRDTs was good, but not excellent, and the MAF was low in some patient groups. By including patients with and without parasitemia, we were able to highlight the possibility that high rates of parasitemia in the population may obscure the diagnosis of non-malaria illness.

In study facilities, the PPV of mRDTs was 78% overall and 82% among febrile patients. These findings are consistent with reported PPVs of 70% to 99% from studies assessing HRP-2-based mRDTs among febrile outpatients in Africa.3,4,29,30 Appropriately, nearly all febrile outpatients attending study facilities were tested for malaria, usually by mRDT. However, a PPV of 78% implies that more than 20% of these febrile patients had a false-positive mRDT result (i.e., positive tests in individuals without malaria infection), which may have led to suboptimal clinical management of non-malaria febrile illnesses. PPVs varied substantially across age groups and sites, with the highest values in school-age children (range, 82–87%) and the lowest values in infants (range, 65–72%). Thus, false-positive mRDTs may have had the greatest impact on infants (in whom PPVs were lowest), and untreated, serious non-malaria fevers may progress more rapidly compared with other age groups.

PPV performance varied according to malaria prevalence. We observed that PPVs increased with age, a finding consistent with those of other studies conducted in settings of moderate and high malaria transmission.3,31 In these settings, older children typically have acquired immunity to clinical malaria illness. This acquired immunity results in chronic parasite carriage8,32 and faster antibody-mediated removal of HRP-2 antigen after parasite clearance,912 both of which may lower the rate of false-positive mRDT results. In addition to age, malaria prevalence also influences PPV. Holding other factors constant, PPVs increase as the background prevalence of disease rises. This tendency was reflected in our data. At all sites, PPVs and TPRs were lowest in infancy, rose through childhood, and then declined in adulthood. Thus, the lower PPVs observed in infants may have, at least in part, been driven by the lower background prevalence of malaria in this age group. Although PPVs are influenced by disease prevalence, we found they were similar across high- and low-transmission sites. Evidence is mixed regarding the relationship between malaria endemicity and PPVs of mRDTs, with the results of some studies indicating higher33 and those of others indicating lower3,34 PPVs in areas of higher malaria transmission.

Malaria illness was attributed to a moderate proportion of fevers in patients with microscopy-confirmed P. falciparum infection at the study facilities, including approximately 50% of fevers in patients 0 to 5 years old and about 20% of fevers in school-age patients. These findings broadly agree with those of a recent multi-country analysis of 24 Sub-Saharan Africa countries in which malaria illness was estimated to account for about 38% of clinic-attended fevers in parasitemic children 0 to 5 five years old.2 Acquisition of immunity to malaria through repeated exposure is thought to be important in shaping trends in MAFs by age, season, and transmission intensity. Findings of most,19,3538 but not all, studies16 indicate an inverse relationship between MAFs and age, as well as between MAFs and transmission intensity.2,15,19 Our findings reflect these trends; in the rural sites, MAFs were greatest in the youngest patients, and were greater in a setting of seasonal (Thyolo) compared with high (Chikhwawa) transmission. In contrast, no clear age- or season-related pattern of MAFs was apparent in urban Ndirande, where malaria infection is associated with recent travel,22 and acquired immunity to malaria may shape patterns in MAFs in complex ways.

MAFs were negligible in school-age patients in some sites and seasons. This finding means that among sick children, fever was more common in those without malaria than in those with malaria; thus, fever may often have been caused by a non-malaria etiology, even if parasitemia was detected. This conclusion is based on population-level estimates but does not provide guidance for diagnosis or treatment of individual patients. Moreover, in areas with negligible MAFs, we cannot infer that malaria did not cause fever in some school-age children, or that malaria protected against fever. Rather, we speculate that among older children with clinical immunity to malaria, non-malaria infections led more frequently to fever than malaria.

The MAFs we observed from the study facilities underscore the conundrum that, although fever is a key symptom driving testing and diagnosis of malaria, malaria illness is frequently not the underlying cause of fever among parasitized patients in endemic settings. Recent molecular diagnostic analyses of outpatient samples in Africa have reported considerable overlap in the occurrence and symptoms of viral, bacterial, and malaria infections in children.3941 But diagnostics for non-malaria illness are virtually absent in outpatient facilities in Africa, and the contribution of non-malaria pathogens to febrile illness in malaria-endemic areas may be widely underappreciated in routine clinical practice. As reported elsewhere,42 we found that febrile patients were more likely to receive a malaria test and be diagnosed with malaria if tested positive. The facilities we surveyed demonstrated appropriate prescribing practices. Almost all patients with positive malaria tests were prescribed an antimalarial medication, and most patients with negative malaria tests were not prescribed one. But, resulting from to a lack of diagnostics for non-malaria illnesses, concurrent non-malaria illnesses were likely considered inadequately, particularly in inpatient groups with the lowest MAFs: school-age children, adults, and urban residents.

Our study had limitations that should be considered when interpreting findings. Parasite detection data used in MAF estimation were obtained from routine clinical microscopy. Such data vary in quality and tend to overdiagnose malaria,43 which would lead to a downward bias in MAF estimates. However, our routine microscopy data were likely of high quality; parasite density values correlated with greater MAFs in young children, a finding that is in accordance with those of several community-based studies.16,19,20 We also observed greater PPVs in febrile patients compared with non-febrile patients—a trend observed in most,16,19,35,4446 but not all,18 studies. However, PPV estimates may have been biased downward by a failure to identify malaria in smears with parasite counts below the limit of detection of routine microscopy. This latter limitation applies to all published reports of the PPVs of mRDTs, and thus does not compromise the generalizability of our data. The proportion of malaria tests conducted by microscopy was greater in Ndirande than in the rural sites. However, this proportion was similar across age groups and seasons, and thus probably did not relate to disease severity or affect the generalizability of findings. Last, details about population characteristics of individuals attending the facilities and care-seeking behaviors were not available in our surveillance protocol.

Using high-quality malaria surveillance data, we demonstrate a high burden of malaria in outpatient settings in Malawi, but also raise the possibility that asymptomatic malaria infection and false-positive mRDT results may lead to considerable overdiagnosis of malaria illness. In these settings, a sizeable proportion of fevers in parasitemic school-age and adult outpatients are likely caused by concurrent non-malaria illness. Many of these non-malaria fevers may be self-limiting and, regardless of MAF values, all patients with a positive malaria test should be treated promptly with first-line antimalarial medication. Nevertheless, failure to diagnosis non-malaria fevers may to lead to treatment delays and may distort assessments of the burden of non-malaria illness.2 Interventions to improve diagnostic accuracy among outpatients in malaria-endemic settings are urgently needed and should include diagnostics for non-malaria fevers, as well as strategies to lower malaria transmission and thus reduce chronic parasitemia among febrile patients.

Supplemental tables

Acknowledgments:

We thank all participants in the study. We also thank the clinical staff at Chikhwawa District Hospital, Thyolo District Hospital, and Ndirande, whose hard work and dedication made this study possible.

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Author Notes

Address correspondence to Miriam Laufer, 685 W Baltimore St., HSF1, Rm. 480, Baltimore, MD 21201. E-mail: mlaufer@som.umaryland.edu

Financial support: This work was supported by the NIH–National Institute of Allergy and Infectious Diseases (U19AI089683 and K24AI114996). We acknowledge the support of the University of Maryland Baltimore Institute for Clinical and Translational Research.

Authors’ addresses: Ingrid Peterson, Center for Vaccine Development and Global Health, University of Maryland Baltimore, Baltimore, MD, and Blantyre Malaria Project, College of Medicine, University of Malawi, Blantyre, Malawi, E-mail: idpet2@gmail.com. Atupele Kapito-Tembo, Andrew Bauleni, and Don P. Mathanga, Malaria Alert Center, College of Medicine, University of Malawi, Blantyre, Malawi, E-mails: atupelekapito@gmail.com, abauleni@mac.medcol.mw, and dmathang@mac.medcol.mw. Osward Nyirenda and Paul Pensulo, Blantyre Malaria Project, College of Medicine, University of Malawi, Blantyre, Malawi, E-mails: omnyirenda@gmail.com and paulpensulo@gmail.com. William Still, Lauren Cohee, and Miriam K. Laufer, Center for Vaccine Development and Global Health, University of Maryland Baltimore, Baltimore, MD, E-mails: wstill@umaryland.edu, lcohee@som.umaryland.edu, and mlaufer@som.umaryland.edu. Clarissa Valim, Department of Global Health, Boston University School of Public Health, Boston, MA, E-mail: clariss.valim@gmail.com. Terrie Taylor, Department of Osteopathic Medical Specialties, College of Osteopathic Medicine, Michigan State University, East Lansing, MI, E-mail: ttmalawi@msu.edu.

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