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    Plot of the running averages of the number of clinical malaria cases (thick line) and the number of times a study participant had a parasitemia > 0 (dotted line), ≥ 300 (dash-dot-dash line), ≥ 3,000 (dash-dot-dot), and ≥ 30,000 (thin solid line) parasites/μL for Donéguébougou in 1999 (A) and 2000 (B) and for Sotuba in 1999 (C) and 2000 (D).

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Year-to-Year Variation in the Age-Specific Incidence of Clinical Malaria in Two Potential Vaccine Testing Sites in Mali With Different Levels of Malaria Transmission Intensity

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  • 1 Malaria Research and Training Center, Department of Epidemiology of Parasitic Diseases, Faculty of Medicine, Pharmacy and Odonto-Stomatology, University of Bamako, Bamako, Mali; Malaria Vaccine Development Branch and Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland

To explore the feasibility of field sites for malaria vaccine trials, we conducted a prospective study of clinical malaria incidence during two consecutive transmission seasons in children and young adults living in two areas of Mali with different entomologic inoculation rates (EIRs). Approximately 200 subjects (3 months to 2 years of age) were enrolled per site and followed weekly. Malaria smears were performed monthly in all participants and when symptoms or signs of malaria were present. In Sotuba (annual EIR < 15 infective bites per person), the incidence of clinical malaria was comparable across all age groups but varied significantly between the 2 years. In contrast, in Donéguébougou (annual EIR > 100 infective bites per person), incidence rates decreased significantly with increasing age but remained stable between years. Our results suggest that, although the age distribution of clinical malaria depends on transmission intensity, the total burden of disease may be similar or higher in settings of low transmission.

INTRODUCTION

Several investigational vaccines targeting the asexual blood stage of Plasmodium falciparum are currently being developed to reduce the mortality and severity of malarial disease, and some have reached advanced stages of clinical testing in endemic areas.1,2 Donéguébougou and Sotuba, two villages in Mali, have been identified as potential sites for Phase 2 testing of malaria vaccines. Development of new antimalarial strategies and vaccines requires an in-depth understanding of the relationships between transmission, immunity, and malaria-related morbidity and mortality. Measuring the age-specific incidence of malaria infection and disease at potential vaccine testing sites is essential to planning future efficacy studies and estimating the sample sizes that will be needed for such trials.

We have previously studied children and young adults in the peri-urban village of Sotuba, located in an area of seasonal malaria transmission with a low entomologic inoculation rate (EIR), and found an unexpectedly high rate of P. falciparum re-infection after treatment with sulfadoxine-pyrimethamine.3 To further explore the relationship between EIR and the age-specific incidence of malaria disease, and also to assess the magnitude of year-to-year variation in the incidence of clinical malaria, we conducted a prospective study during the malaria transmission seasons (July to December) of 2 consecutive years (1999 and 2000) in children and young adults living in the villages of Donéguébougou and Sotuba, which historically have different EIRs.

MATERIALS AND METHODS

Study sites.

This study was conducted concurrently in the villages of Donéguébougou and Sotuba in Mali. Both sites are located in the North Sudanian savannah region of Mali. Malaria transmission occurs mainly during the rainy season that extends from June to November, with annual recorded rainfall ranging from 700 to 1,200 mm. There is essentially no malaria transmission at either site during the dry season (January to June) (Y. T. Toure, unpublished results).

Donéguébougou is a rural village of ∼1,200 inhabitants that is located 30 km northeast of Bamako, the capital city of Mali. The village is accessible by unpaved roads that become difficult to navigate during the rainy season. The Malaria Research and Training Center (MRTC) of the University of Bamako operates a medical clinic in the village and an adjacent clinical laboratory, which serves as the primary source of medical care in the surrounding area.

In contrast, Sotuba is a peri-urban village located on the outskirts of Bamako on the bank of the Niger River, consisting of ∼2,600 inhabitants. Malaria transmission follows the same seasonality as in Donéguébougou, although EIRs are historically much lower. As in Donéguébougou, the MRTC maintains a medical clinic in Sotuba.

Study design.

The study was conducted from 1999 to 2000. Children and young adults between the ages of 3 months and 20 years were enrolled at the beginning of each of two successive malaria transmission seasons. Approximately 200 subjects were randomly chosen at each site from a full village census and were invited to participate in the study. Participation during the first year of the study did not preclude inclusion in the second year of the study.

Participants were seen weekly throughout the malaria transmission season extending from July to December of each year. At each visit, participants were questioned for symptoms of malaria and examined. Hemoglobin measurements and thick blood smears were prepared from capillary blood obtained by fingerprick at the first visit of each year, and every 4 weeks thereafter (designated “monthly” visits); smears were not read contemporaneously unless symptoms or signs of malaria were present. At the other regularly scheduled weekly visits, malaria smears were only performed (and read immediately) if signs or symptoms of malaria were present. In addition to the scheduled weekly visits, subjects were encouraged to visit the clinic at any time if ill.

If symptoms or signs compatible with malaria were present, fingerprick blood was collected for hemoglobin measurement and a blood film, which was read immediately. Thus, parasitemic episodes could be first detected at three different types of visit: at asymptomatic monthly visits, symptomatic weekly visits (including monthly visits), and symptomatic unscheduled visits. Clinical malaria was defined as the presence of fever (axillary temperature ≥ 37.5°C) or another symptom or sign compatible with malaria (i.e., history of fever or chills, headache, seizures, vomiting, lethargy, or diarrhea) plus the presence of asexual Plasmodium spp. of any density on a thick blood film, in the absence of another cause of the illness.

Cases of uncomplicated malaria were treated with a single, weight-adjusted dose of sulfadoxine-pyrimethamine, whereas cases of severe malaria were treated with parenteral quinine.4 Subjects were followed on Days 1, 2, 3, 7, and 14, and malaria smears were performed on Days 3, 7, and 14 after treatment.

Community permission for the study was obtained from village elders,5 and the study was approved by the ethical review committees of the Faculty of Medicine, Pharmacy, and Dentistry at the University of Bamako (Mali) and the National Institutes of Allergy and Infectious Diseases (Bethesda, MD). Individual written informed consent was obtained from all participants or their guardians.

Laboratory testing.

Hemoglobin concentrations were determined using a portable analyzer (Hemocue, Lake Forest, CA). Parasitemia was assessed by counting the number of asexual P. falciparum parasites on Giemsa-stained thick blood films until 300 leukocytes were observed. Parasite densities were converted to parasites per microliter of blood, assuming an average leukocyte count of 7,500/μL. Routine quality control was performed on 10% of the slides, with a second microscopist re-examining the blood films while blinded to the previously recorded result. Differences in parasitemia of > 10% were resolved by an expert microscopist.

Entomologic studies.

Surveys were performed monthly from June to December of each year. Mosquitoes were collected using both the pyrethrum insecticide spray catch (PSC) method in human dwellings and the human landing catch (HLC) method. PSC collections were performed in a randomly selected sample of 60 individual residences, and HLC collections were undertaken between 6:00 pm and 6:00 am both indoors and outdoors by mouth aspirator at two collection points in each village. Selected houses were marked and visited every month. Mosquitoes were speciated by morphologic features and classified by abdominal development stage. Identification of blood meal source (human versus non-human) and detection of circumsporozoite (CSP) antigen were assessed by ELISA using standard methods.6 Monthly person-biting rates were obtained by multiplying the daily person-biting rate by 30 days for each month. The monthly EIR was obtained by multiplying the monthly person-biting rate by the CSP positivity rate. The cumulative annual EIR was calculated as the sum of the monthly EIRs.

Statistical analysis.

Analyses were performed using Stata software, version 8 (StataCorp, College Station, TX) and Microsoft Excel (Microsoft, Redmond, WA). At enrollment, study participants were classified into the following age groups: 0–5, 6–10, 11–15, and 16–20 years. Age-specific incidence rates (the number of episodes per person over the transmission season) of clinical malaria were calculated by study site and year of study. Because the distribution of malaria episodes followed a Poisson distribution, generalized estimating equations for the Poisson family were used to take into account non-independence of the episodes in comparisons of incidence rate ratios between age groups and sites. Proportions were compared using the χ2 or Fisher exact test as appropriate. P ≤ 0.05 was considered significant for all tests.

To graphically assess trends in the number of detected parasitemic episodes per year and the incidence of clinical malaria as a continuous function of age, data were plotted as running averages. For each subject, the number of detected infections with any parasitemia or a parasitemia > 300, 3,000, or 30,000/μL was counted. Episodes detected by both active and passive case detection were included. The number of times each subject was treated for malaria was also counted. For each category, the running average used was the mean of 21 consecutive subjects in order of increasing age, plotted at the age of the 11th subject. Thus, the first plotted point for number of episodes > 3,000/μL is the mean value of the number of times the 21 youngest subjects had a parasitemia > 3,000/μL, the second plotted point, subjects 2–22, the third plotted point, subjects 3–23, and so on.

RESULTS

Characteristics of the study participants.

Three hundred ninety-seven (196 in Donéguébougou and 201 in Sotuba) and 398 (199 in Donéguébougou and 199 in Sotuba) children were enrolled in 1999 and 2000, respectively. Table 1 summarizes the age and sex distributions of study participants, as well as the proportion lost to follow-up, by village and study year. The cohorts were comparable with respect to age and sex distribution in the two villages during the 2 years of the study. The mean age at enrollment including all the participants was 9.8 ± 5.9 (SD) years, and 52.1% were male. The percentages of participants lost to follow-up were similar between villages and years except in Sotuba in 1999, where a significantly higher proportion (15.9%; P < 0.01) was lost to follow-up compared with 7.5% in the same village in 2000 and 4.5% and 4.6% in Donéguébougou in 1999 and 2000, respectively. The overall percentage of participants lost to follow-up during the 2 years of the study was 8.2%.

Transmission vectors and entomological inoculation rates.

Although malaria was transmitted by both An. gambiae s.l. and An. funestus, the predominant species in both villages was An. gambiae s.l., which accounted for 99.7% of transmission in Sotuba and 91.6% in Donéguébougou in 2000. In 1999, these proportions were 100% and 99.5%, respectively.

Monthly and cumulative EIRs are summarized in Table 2. The cumulative EIR by the PSC method from June to December 1999 in Donéguébougou was 21.1 infective bites/person, which decreased slightly to 19.2 in 2000. In Sotuba, the cumulative EIR using the same method was 0.72 in 1999 but decreased in 2000 to 0.28 infective bites/person. Results using the HLC method showed the same pattern, with a slight decrease in Donéguébougou from 1999 to 2000 (167.23 infective bites/person in 1999 versus 137.30 infective bites/person in 2000) and a more marked reduction in Sotuba (12.25 infective bites/person in 1999 versus 3.64 infective bites/person in 2000). Overall, the cumulative EIRs were 13.7 and 29.3 times higher in Donéguébougou than Sotuba in 1999 and 37.7 and 68.7 times higher in 2000, using the HLC and PSC methods, respectively.

Malaria parasitemia.

The prevalences of parasitemia at the monthly visits, categorized by discrete age groups, are summarized in Table 3. Of the 4,370 monthly smears, 2,170 were obtained in 1999 and 2,200 in 2000. In 1999, the average prevalence of parasitemia during the transmission season was 54.1% in Donéguébougou and 15.1% in Sotuba compared with 48.3% in Donéguébougou and 6.1% in Sotuba in 2000. As expected, the proportion of positive smears was significantly higher in Donéguébougou in all age groups during both years of the study (P < 0.001, χ2). The average prevalence of parasitemia did not vary significantly by age group in Sotuba in 1999 or in 2000, whereas in Donéguébougou, parasite prevalence varied significantly with age (P < 0.001, χ2) during both years of the study, with the highest parasite prevalence observed in children in the 6- to 10-year age category.

To enable the use of actual ages of study participants instead of grouping them into age categories, running averages of the number of parasitemic episodes per subject as a continuous function of age are plotted in Figure 1, including data from both scheduled and unscheduled visits. Smears obtained to assess parasitemia within 14 days of treatment were excluded from the analysis. Curves are plotted for parasite densities exceeding 0, 300, 3,000, and 30,000 parasites/μL of blood. Also shown are the running averages of the number of times each person was treated for malaria. In Donéguébougou, there was a broad age range (∼3–10 years) over which subjects had the maximum number of positive blood films in both 1999 and 2000 (i.e., the number of films per year with parasite densities > 30 parasites/μL). The age at which the maximum number of episodes per year occurred shifted to younger ages as episodes with higher parasite densities were considered. However, even for episodes with relatively high parasite densities (e.g., those > 30,000/μL), the age at which most such infections were detected was ∼2–3 years of age (Figure 1, A and B). In Sotuba, on the other hand, the number of parasitemic episodes per person per year showed little correlation with age, regardless of the parasite density considered.

Incidence of clinical malaria.

A total of 1,109 episodes of clinical malaria were recorded during the two transmission seasons at the two study sites (533 in Donéguébougou and 576 in Sotuba). No cases of severe malaria or deaths caused by malaria were recorded during the periods of surveillance. Table 4 shows the incidence of clinical malaria by age category and year at the two sites. In Donéguébougou, the incidence of clinical malaria decreased significantly with increasing age (trend, P < 0.001), with the highest incidence of clinical malaria seen in children between the ages of 0 and 5 years and the lowest in those between 16 and 20 years of age. The age-specific incidence of clinical cases closely paralleled the prevalence of moderate to high parasitemia as measured by the number of blood films per person with a parasite density > 3,000/μL (Figure 1). The incidence of clinical malaria was stable during the 2 consecutive years in all age groups. In Sotuba, the age-specific incidence of clinical malaria was similar between age groups, but there was a significant reduction in the incidence of clinical malaria in 2000 compared with 1999 (P < 0.001) in all age groups (Table 4; Figure 1).

When comparing the two villages, the incidence of clinical malaria in 1999 was similar in the two villages for subjects 0–5 years of age but was higher in Sotuba (the low EIR setting) than in Donéguébougou (the high EIR setting) in all other age categories (i.e., 6–10, 11–15, and 16–20 years; P ≤ 0.019). In contrast, in 2000, the age-specific incidence of clinical malaria was significantly lower in Sotuba compared with Donéguébougou in subjects between 0 and 5 years of age (P < 0.001) but was similar between the two villages in the other age categories.

The percentage of malaria cases diagnosed at unscheduled visits was similar in both villages and for both years (Donéguébougou: 54% and 48% for 1999 and 2000, respectively; Sotuba: 55% and 50% for 1999 and 2000, respectively) and showed no significant age dependence. However, there was a marked difference between the two villages in the proportion of episodes of parasitemia that were accompanied by symptoms or signs of malaria. In Donéguébougou, 33% and 35% of positive blood films were accompanied by symptoms in 1999 and 2000, respectively, whereas in Sotuba, the percentages were much higher at 74% and 86%, respectively.

DISCUSSION

As more and more candidate malaria vaccines become ready for clinical testing in endemic areas, the identification and development of field sites for such trials is urgently needed. For Phase 2b and 3 studies, knowledge of a site’s baseline incidence of malaria infection and disease, as well as the dynamics of exposure and transmission from mosquitoes, is essential to the design of vaccine trials and the calculation of required sample sizes. We assessed two potential vaccine-testing sites in Mali with different transmission rates, resulting in different patterns of infection and disease in the children and young adults that were studied. This study is one of few that have prospectively followed established cohorts for both disease incidence and transmission intensities during the same period of time and in an identical fashion, allowing for a rigourous comparison between the two sites.

In the peri-urban village of Sotuba, with an annual EIR of < 15 infective bites per person (HLC method), there was little evidence of either anti-disease or anti-parasite immunity in individuals between the ages of 0 and 20 years. Most of the parasitemic episodes detected were accompanied by symptoms severe enough to prompt treatment. In areas with low EIR, the parasite prevalence and frequency of disease are nearly proportional to the EIR. As the EIR increases, parasite prevalence and the frequency of disease both increase, but rapidly approach saturation levels after which further increases do not occur.7 Consistent with this pattern, the incidence of clinical malaria and the incidence of parasitemic episodes in the low EIR setting of Sotuba closely paralleled the changes in EIR between 1999 and 2000. The decrease in EIR was presumably caused by the substantial difference in the mosquito biting rates between 1999 and 2000, which in turn was likely because of the low amount of rainfall (792.5 mm) recorded during the 1999 rainy season compared with 1,143.8 mm in 2000. In contrast, the population in Donéguébougou, a rural village with an annual EIR of > 100 infective bites per person, showed evidence of substantial anti-disease and anti-parasite immunity.

The intensity of malaria transmission is known to affect the age-specific incidence of malaria and the patterns of disease expression; this has been especially well-established for severe malaria. In areas of less intense transmission, the burden of disease is relatively more common in older children, with cerebral malaria being the main manifestation of severe malaria, whereas in areas with intense and perennial transmission, the burden of malaria is borne mostly by younger children with severe anemia being the predominant manifestation of severe disease.813 In Donéguébougou, the incidence of clinical malaria was highest in the youngest age group and decreased significantly with increasing age, whereas in Sotuba, the incidence of clinical malaria was similar among age groups, leading to higher overall malaria morbidity than in Donéguébougou in 1999.

These results are consistent with previous studies in which low- and high-transmission areas were compared using a design similar to this study: one in Senegal and the other in coastal Kenya. In the Senegalese study, two villages (Dielmo and Ndiop) with markedly different intensities of malaria transmission were compared. At the site with intense and perennial transmission, the bulk of the morbidity caused by malaria was concentrated in the younger age groups, and little disease was observed after the age of 10 years, whereas in the village with low-intensity transmission, significant rates of disease occurred well into adolescence and adulthood.11,14,15 Similarly, at two sites in the Kilifi district of Kenya, the fraction of fevers attributable to malaria was higher in infants (< 1 year old) at the high-transmission site than the low-transmission site, but the opposite was true for children between the ages of 5 and 19 years.16 As in our study, a higher number of episodes of clinical malaria per person per year in people from the area of low transmission was seen compared with the number of episodes in those from the higher-transmission area.

Blood-stage malaria vaccines are intended to reduce severe disease and mortality in infants and young children through one or both of two mechanisms: by priming the immune system to develop more effective immunity when boosted by subsequent natural infections or by boosting the pre-existing immunity induced by natural infections. With many potential vaccines approaching the stage of advanced clinical testing, there is a need for an efficient Phase 2 trial design that will enable rapid selection of the best candidates for further study. For practical reasons, the current practice is to use endpoints such as the frequency of uncomplicated clinical malaria or the frequency of parasitemic episodes rather than severe malaria or death. This choice of endpoints is based on the assumptions that they will predict vaccine efficacy in reducing the severe morbidity and mortality caused by malaria. In this regard, both Sotuba and Donéguébougou provide interesting possibilities for Phase 2 vaccine testing.

Although the desired target group for a blood-stage malaria vaccine is infants, conducting Phase 2 trials in this age group is difficult in endemic areas because of the high incidence of concomitant illness, the administration of other routine childhood vaccines, and low malaria attack rates. Paradoxically, children of all ages in Sotuba had relatively high attack rates for potential endpoints (parasitemia and disease) with low levels of immunity and may therefore provide a useful population for testing the ability of blood stage vaccines to induce protective responses in relatively naïve infants. It may even be possible to test the vaccine in adults in this epidemiologic setting. The difficulty in conducting a trial in a low seasonal transmission village, such as Sotuba, is the potential variability of the EIR from 1 year to another, making it more difficult to predict the required sample size.

In contrast, sites with higher levels of seasonal transmission, such as Donéguébougou, provide ideal sites for testing vaccines designed to enhance the immunity induced by previous infections. The incidence rates of several possible outcome measures (e.g., clinical malaria, parasitemia > 3,000/μL) were high in the desired target group of young children (Figure 1), so that relatively small group sizes could be used. These children are still at major risk of severe malaria, and the incidence of relatively high parasite densities and clinical malaria was still much greater than in older inhabitants of the village. Thus, there is the potential for an effective vaccine to produce a substantial and measurable reduction in malaria-related morbidity.

The ability to undertake a vaccine trial, or any long-term, relatively intensive surveillance program depends not only on the epidemiology of malaria but also on the community attitudes to the study and study team. As judged by many criteria, including the high retention rate in this study (especially in Donéguébougou), these communities see malaria as a major problem and their commitment makes these ideal locations for vaccine trials.

In summary, our results suggest that when the incidence of malaria disease is measured in all age groups, the total morbidity attributable to malaria may be even higher in settings of low transmission. However, in areas of low transmission intensity, changes in rainfall may lead to more dramatic changes in EIR, and consequently to significant changes in disease incidence from year to year. In areas with high-transmission intensity, disease incidence is more stable from year to year, and therefore data from prior years can be used to reliably estimate the sample sizes required for vaccine trials.

Table 1

Patient population

19992000
Age categories (years)Donéguébougou (N = 196)Sotuba (N = 201)Donéguébougou (N = 199)Sotuba (N = 199)Total (N = 795)
0–5 (%)53 (27.0)58 (28.9)53 (26.6)51 (25.6)215 (27.0)
6–10 (%)48 (24.5)49 (24.4)52 (26.1)53 (26.6)202 (25.4)
11–15 (%)52 (26.5)48 (23.9)51 (25.6)49 (24.6)200 (25.2)
16–20 (%)43 (21.9)46 (22.9)43 (21.6)46 (23.1)178 (22.4)
Sex
    Male (%)104 (53.1)97 (48.3)107 (53.8)106 (53.3)414 (52.1)
Lost to follow-up (%)9 (4.6)32 (15.9)9 (4.5)15 (7.5)65 (8.2)
Table 2

Monthly and cumulative EIRs by the PSC and HLC methods in Donéguébougou and Sotuba during the malaria transmission seasons of 1999 and 2000

19992000
DonéguébougouSotubaDonéguébougouSotuba
MonthBiting rate*EIRBiting rateEIRBiting rateEIRBiting rateEIR
* Biting rate of An. gambiae only. An. funestus contributed < 5% of the EIR at all time points.
PSC
    June1.00.006.40.002.20.092.40.00
    July28.60.9739.60.286.20.222.40.02
    August71.32.2812.60.0447.01.697.40.07
    September150.55.1217.10.03112.96.3210.20.14
    October90.34.0620.10.1646.37.782.70.05
    November34.77.094.40.2122.92.501.00.00
    December7.01.572.90.009.90.633.70.00
    Total383.421.09103.10.72247.419.2329.80.28
HLC
    June0.00.008.70.001.90.083.60.00
    July127.54.34242.41.7015.00.548.70.09
    August791.225.32410.11.23613.122.07156.31.41
    September1582.553.818341.671042.558.40136.21.91
    October1308.758.89692.45.54238.142.5612.30.23
    November91.920.83452.1295.611.415.10.00
    December13.14.0523.70.0020.62.2611.10.00
    Total3914.9167.232256.312.252026.8137.30333.33.64
Table 3

Average prevalence of P. falciparum infection at routine monthly visits by age group per site and year of study

DonéguébougouSotuba
YearAge (years)No. of smearsPercent positiveNo. of smearsPercent positiveP value
NS, not significant.
1999Overall102854.1114215.1< 0.001
0–530939.532514.5< 0.001
6–1027967.729217.1< 0.001
11–1522366.428416.6< 0.001
16–2021746.124112.0< 0.001
P value for trend< 0.001NS
2000Overall109748.311036.1< 0.001
0–528738.32724.0< 0.001
6–1029160.82997.4< 0.001
11–1529052.42724.8< 0.001
16–2022939.72608.0< 0.001
P value for trend< 0.001NS
Table 4

Age-specific incidence rates and IRRs of clinical malaria per village and per year of study

DonéguébougouSotuba
YearAge (years)No. subjectsNo. casesPerson-season of follow upIncidence rate per seasonIRRIRR 95% CINo. subjectsNo. casesPerson-season of follow upIncidence rate per seasonIRRIRR 95% CI
1999Overall196262189.51.38201379191.62.06
0–55310650.52.1Ref589551.41.8Ref
6–104867481.40.670.55–0.80499747.821.090.91–1.31
11–15526050.41.20.570.46–0.704810145.42.21.21.00–1.44
16–20432940.60.70.340.24–0.47468638.92.21.21.00–1.43
P value for trend< 0.001NS
2000Overall199271194.31.39199197191.61.02
0–55310452.12Ref513846.90.8Ref
6–105285521.60.820.66–1.01536752.41.31.581.14–2.18
11–15515150.110.510.39–0.66494546.911.190.83–1.69
16–20433140.10.80.390.28–0.54464745.411.280.90–1.81
P value for trend< 0.001NS
Figure 1.
Figure 1.

Plot of the running averages of the number of clinical malaria cases (thick line) and the number of times a study participant had a parasitemia > 0 (dotted line), ≥ 300 (dash-dot-dash line), ≥ 3,000 (dash-dot-dot), and ≥ 30,000 (thin solid line) parasites/μL for Donéguébougou in 1999 (A) and 2000 (B) and for Sotuba in 1999 (C) and 2000 (D).

Citation: The American Journal of Tropical Medicine and Hygiene Am J Trop Med Hyg 77, 6; 10.4269/ajtmh.2007.77.1028

*

Address correspondence to Ogobara K. Doumbo, University of Bamako, Faculty of Medicine, Pharmacy and Odonto-Stomatology, B.P. 1805 Bamako, Mali. E-mail: okd@mrtcbko.org

Authors’ addresses: Alassane Dicko, Issaka Sagara, Moussa Sogoba, Mohamed B. Niambele, Adama Dao, Guimogo Dolo, Daniel Yalcouye, Dapa A. Diallo, and Ogobara K. Doumbo, Malaria Research and Training Center, Department of Epidemiology of Parasitic Diseases, Faculty of Medicine, Pharmacy and Dentistry, University of Bamako, PO Box 1805, Bamako, Mali, Telephone: 223-222-8109, Fax: 223-222-4987, E-mails: adicko@mrtcbko.org, isagara@mrtcbko.org, msogoba@mrtcbko.org, jballa@mrtcbko.org, adama@mrtcbko.org, dolo@mrtcbko.org, msogoba@mrtcbko.org, dadiallo@mrtcbko.org, and okd@mrtcbko.org. David Diemert, Human Hookworm Vaccine Initiative, Sabin Vaccine Institute, 1889 F Street, NW, Suite 200S, Washington, DC 20006, Telephone: 202-842-8467, Fax: 202-842-8467, E-mail: david.diemert@sabin.org. Allan Saul, Laboratory of Malaria and Vaccine Research, NIAID/NIH, Twinbrook III, Room 1E-04, 12735 Twinbrook Parkway, Rockville, MD 20852, Telephone: 301-594-2701, E-mail: ASaul@niaid.nih.gov. Louis H. Miller, Malaria Vaccine Development Branch, NIAID, NIH Twinbrook 1, Room 1111, 5640 Fishers Lane, Rockville, MD 20852, Telephone: 301-435-2177, Fax: 301-480-1958, E-mail: lomiller@mail.nih.gov. Yeya T. Toure, Malaria Research and Training Center, Department of Epidemiology of Parasitic Diseases, Faculty of Medicine, Pharmacy and Dentistry, University of Bamako, PO Box 1805, Bamako, Mali, Telephone: 223-222-8109, Fax: 223-222-4987, E-mail: tourey@who.int. Amy D. Klion, Bldg. 4, Rm. 126, National Institutes of Health, 4 Center Drive, Bethesda, MD 20892, Telephone: 301-435-8903, Fax: 301-480-3757, E-mail: aklion@nih.gov.

Acknowledgments: The authors thank the populations of the two villages for cooperation throughout the study, Mahamadou Thera, Mamadou Ba, Aldiouma Guindo, Mady Sissoko, and Mahamadou Assadou for help in the field and in the laboratory, and Richard Sakai and Souleymane Karembé for logistical support.

Financial support: This study was supported by the NIAID Intramural Program.

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