j.1365-3156.2003.01053.x

Inland valley rice production systems and malaria infection

and disease in the savannah of Cote dIvoire

M.-C. Henry1, C. Rogier2, I. Nzeyimana1, S. B. Assi1, J. Dossou-Yovo1, M. Audibert3, J. Mathonnat3, A. Keundjian2,

E. Akodo4, T. Teuscher4 and P. Carnevale1

1 Institut P. Richet, Bouake, Cote dIvoire2 Institut de Medecine Tropicale du Service de Sante des Armees, Marseille, France3 CERDI/CNRS, Clermont-Ferrand, France4 WARDA, Bouake, Cote dIvoire

Summary In sub-Saharan Africa, lowlands developed for rice cultivation favour the development of Anopheles

gambiae s. l. populations. However, the epidemiological impact is not clearly determined. The

importance of malaria was compared in terms of prevalence and parasite density of infections as well

as in terms of disease incidence between three agroecosystems: (i) uncultivated lowlands, R0, (ii)lowlands with one annual rice cultivation in the rainy season, R1 and (iii) developed lowlands with twoannual rice cultivation cycles, R2. We clinically monitored 2000 people of all age groups, selectedrandomly in each agroecosystem, for 40 days (in eight periods of five consecutive days scheduled every

6 weeks for 1 year). During each survey, a systematic blood sample was taken from every sick and

asymptomatic person. The three agroecosystems presented a high endemic situation with a malaria

transmission rate of 139158 infective bites per person per year. The age-standardized annual malaria

incidence reached 0.9 malaria episodes per person in R0, 0.6 in R1 and 0.8 in R2. Children from 0 to

9-year-old in R0 and R2 had two malarial attacks annually, but this was less in R1 (1.4 malaria episodes

per child per year). Malaria incidence varied with season and agroecosystem. In parallel with

transmission, a high malaria risk occurs temporarily at the beginning of the dry season in R2, but

not in R0 and R1. Development of areas for rice cultivation does not modify the annual incidence of

malarial attacks despite their seasonal influence on malaria risk. However, the lower malaria morbidity

rate in R1 could be explained by socio-economic and cultural factors.

keywords malaria morbidity, rice cultivation systems, savannah, Cote dIvoire

Introduction

In sub-Saharan Africa, water resource development

projects affect many waterborne diseases. In the case

of malaria, irrigated rice cultivation favours the

multiplication of anopheline vectors. However, the

epidemiological impact of rice cultivation varies

according to the local malaria situation (Carnevale et al.

1999). It can be associated with an increase in

malaria transmission and morbidity, as in Burundi

(Coosemans 1985) and the uplands in Madagascar

(Laventure et al. 1996). Conversely, irrigated rice

cultivation does not seem to affect malaria transmission

or its incidence in northern Cameroon (Audibert et al.

1990), in the Senegal River valley (Faye et al. 1993,

1995), in the Kou valley in Burkina Faso (Boudin

et al. 1992) and in the Gambia River valley (Lindsay

et al. 1991).

Most of these studies limit themselves in explaining

aspects of relations between irrigated rice cultivation,

transmission level, Plasmodium infections and malaria

morbidity at the local level. However, to predict the

consequences of rice cultivation development and to

control its possible negative aspects, it is necessary to

improve understanding of the interrelations between public

health, the environment and irrigated zones (Gioda 1992).

Thus, an interdisciplinary study of relationships between

lowland cultivation systems and malaria was conducted at

regional level in three West African important settings:

Sahel, savannah and forest. This study was carried out in a

savannah region of northern Cote dIvoire. Its objective

was to compare malaria pressure in three farming systems

in terms of prevalence and parasite density of infections,

and also in terms of clinical malaria incidence. Exposure to

transmission by Anopheles was the object of another study

(Dossou-Yovo et al., unpublished data).

Tropical Medicine and International Health

volume 8 no 5 pp 449458 may 2003

2003 Blackwell Publishing Ltd 449

Materials and methods

Study zone

The study was conducted in the savannah region of northern

Cote dIvoire, where population density was 2040

inhabitants per km2. All villages were classified according

to the farming systems in their surrounding valleys within a

two km radius: no (rice) cultivation (R0); no water control,

suitable for one cycle of rice cropping during the rainy

season (R1); partial or full water control that permits two

cycles of rice cropping per year (R2). The three categories

of farming practice are referred to below as agroecosys-

tems. The 8 study villages per farming system were

randomly selected among villages pooled by agro-

ecosystem. All R1 and R2 villages were situated in the

Departement of Korhogo where all lowlands were culti-

vated. The 8 R0 villages were situated in the Departement

of Katiola, where lowlands were not at all farmed. The R2

villages were Gbahouakaha, Kohotieri, Koumbolikaha,

Lamekaha, Nambekaha, Nombolo, Nongotchenekaha and

Zemongokaha; for R1, the villages were Binguebougou,

Fapaha, Kombolokoura, Kaforo, Karakpo, Kassoumbarga,

Katiorkpo, Tioro and for R0, Angolokaha, Doussoulo-

kaha, Folofonkaha, Kabolo, Ounadiekaha, Petionara,

Serigbokaha, Timorokaha. There was a health centre in

Petionara (R0), Tioro (R1) and Gbahouakaha (R2) and a

village health post in Kohotieri (R2).

The total population required for a Poisson regression

analysis was estimated using Egret Siz (ver. 1, 1993) to

be 80 000 person-days to detect a relative risk below 0.5

with a power of 80%, a significance level of 5%, a

maximum incidence of 0.64 malarial attacks per person-

year in the reference ecosystem (Trape et al. 1994) and

including 30% of participants lost to follow-up. This

total was attained by selecting 250 persons in each

village and monitoring them clinically for 40 days

distributed over eight periods of five consecutive days

scheduled every 6 weeks in the year.

People were selected from randomly sampled com-

pounds by dividing the village in districts. Of these, six

districts were randomly chosen irrespective of the chiefs

district. Then, from the centre of each of these six districts

a cardinal direction was randomly selected. In this direc-

tion, the first six encountered compounds were selected.

If there were less than six compounds in this direction,

another direction was randomly selected. Each family head

and each person included in the study or their legal

guardian gave informed consent. Ethical approval for the

project was given by the Ivorian Ministry of Public Health.

During the monitoring periods, patients of villages parti-

cipating or not in the study were treated free of charge by

the medical team.

Data collection

The active case detection (ACD) surveys for malaria

episodes started on 18 March 1997, 26 April, 10 June,

22 July, 2 September, 18 October, 25 November and

20 January 1998. During these monitoring periods, a nurse

assisted by two health workers from the village trained for

the purpose of the study, visited all households covered by

the study every day. A doctor provided permanent super-

vision of the teams. The presence, absence and health

condition of each included person were recorded daily by

the assistant nurse on a sheet meant for each household.

The nurse examined any detected sick person at home

and registered clinical observations on an ad-hoc sheet.

A blood sample was taken systematically and patients were

treated according to the clinical diagnosis made by the

nurse. When malaria was suspected, the patient was

treated with chloroquine at the dose of 25 mg/kg body

weight for 3 days in conformity with the National Program

for Malaria Control. ACD was scheduled 15 days after

the malaria transmission assessment carried out in 12 of

the 24 villages clinically monitored, in order to correlate

malaria infection and disease rates with transmission rates.

The cross-sectional surveys (CSS) were held during each of

the eight monitoring periods, a blood sample was taken

systematically from each asymptomatic person in the

study. This was carried out on the second day of each

period to make sure that a participant classified as

asymptomatic was free of illness during the days before

and after the blood sample was taken.

Laboratory procedures

Thick smears were made from blood samples and stained

with Giemsa in the field and examined using a microscope

(ocular 10, lens 100) at Institut Pierre Richet at Bouake.Plasmodium species were identified and asexual forms of

each species counted on 200 leucocytes. The parasite

density was calculated by assuming an average concentra-

tion of 8000 leucocytes/ll of blood. The same experiencedtechnician, under the supervision of a parasitologist,

examined the smears from a given village. The six

technicians also compared the same set of blood samples.

Their rate of parasite detection and parasite density

estimates did not differ significantly. A randomly selected

10% sample of the thick smears was double-read for

quality control.

A urine study of antimalarial drugs was conducted in

January 1998 on more than 20 adults and children over

2 years old randomly selected in each village. The urine

collected was tested at the Institut de Medecine Tropicale

du Service de Sante des Armees at Marseille through a

Tropical Medicine and International Health volume 8 no 5 pp 449458 may 2003

M.-C. Henry et al. Inland valley rice production and malaria

450 2003 Blackwell Publishing Ltd

high-performance liquid chromatography technique

(Brown et al. 1982), modified for simultaneous isolation

and measure of chloroquine and its metabolites, amo-

diaquine, sulfamide and quinine.

Analytical strategy

Demographic, clinical, parasitological and attendance data

were double-entered independently in an Access database

(ver. 7, 1995). Data were analysed using EpiInfo (ver. 6,

1995), STATA statistical package (StataCorp 2001) and

Egret (ver. 2, 1999) software programs.

The association between the parasite load and the

occurrence of clinical episodes was tested using a random-

effect logistic regression model for each agroecosystem

and taking clinical status (pathological episode vs.

asymptomatic state) as dependent variable, and parasite

density, age and season as independent variables. In this

type of model, a random intercept variable is allowed to

vary with subjects and this random subject-specific inter-

cept allows taking into account the interdependency of

observations made on the same person. The independent

variables and their interaction terms were tested and kept

in the model when their effects were significant (likelihood

ratio statistic, P < 0.05). For each pathological period, the

probability that it was caused by malaria was estimated

through the attributable fraction calculated from the odds

ratios associated with the estimated parasite density in

each logistic model (Armstrong Schellenberg et al. 1994).

Pathological episodes considered were those characterized

by a high axillary temperature (37.5 C), a body hot tothe touch, sweat, shiver, headache, nausea or vomiting

(Rogier et al. 1999) or by a history of fever during the

48 h preceding the first day of ACD; or in cases of infants,

anorexia or any pathological condition described by the

mother (Smith et al. 1995). For individuals and given

periods, the number of malarial attacks was estimated by

the sum of probabilities of pathological episodes that were

caused by malaria, depending on the parasite load.

Malaria incidence density was calculated through the ratio

of pathological episodes attributable to malaria and

villagers person-days present during monitoring periods.

The clinical malaria incidence in a standardized popula-

tion was calculated, for each agroecosystem, by multiply-

ing age specific incidence densities estimated in each

category with the number of subjects belonging to age

groups of a virtual population of 1000 persons with an

age-distribution identical to the age-distribution of the

populations of the three studied agroecosystems as a

whole.

Parasitological data were analysed separately in terms of

(1) prevalence of Plasmodium falciparum, P. malariae and

P. ovale asexual blood forms, (2) density of P. falciparum

asexual blood forms in parasite-positive thick smears, and

(3) prevalence of P. falciparum gametocytes.

Only one blood sample per person per monitoring period

was considered for the analysis. When a pathological

condition was detected, it was the blood sample taken

during the clinical episode that was retained. When several

blood samples from an asymptomatic period were avail-

able, one was randomly selected for analysis.

We used a generalized estimating equation (GEE)

approach for statistical analysis of repeated measures

(Zeger & Liang 1986), which can be used with normal

distributions and discrete data. We used an exchangeable

correlation structure in which the correlation between

observations made on the same person at different times is

assumed to be the same. The differences were tested by the

Wald test and 95% confidence intervals were calculated.

The prevalence of asymptomatic malaria infections was

analysed as a binomial response. The positive asympto-

matic parasite density was log transformed and analysed

with a link function for a normally distributed response.

The GEE approach allows some departure from the

hypothesis about the distribution of the dependent variable

and gives robust estimates of regression coefficients taking

into account the interdependence of observations made

within the same person. Comparisons between prevalences

and between parasite densities were performed by

chi-square test and variance analysis. For parasite densities,

interactions between age and agroecosystem and between

season (dry season from November to April, and rainy

season from May to October) and agroecosystem were

tested using a multiple linear regression model. Clinical

malaria incidence densities observed for the different

categories, in the different age classes (09 and 10 years)and in the different seasons were compared using the

likelihood ratio statistic in a Poisson regression model,

with the estimated number of malarial attacks as depend-

ent variable and the cumulative number of monitoring days

as exposure variable. The village incidence mean rates were

compared between each pair of villages categories using

MannWhitney U-test. Statistical tests were considered as

significant when P < 0.05.

Results

Population description

From 18 March 1997 to 28 February 1998, 6184 people in

24 villages (2054 in eight villages of farming system R0,

2055 in eight villages of R1, and 2075 in eight villages

of R2) were clinically and parasitologically monitored.

Children born during the study were not included. The




distribution of population samples by age is shown in

Table 1. The sample in R0 was younger than in R1 and R2.

The sex ratio was unbalanced for adults, particularly in R1

and R2. The female/male ratio was 1.2 in R0, and 1.7 in

R1 and R2. The population of the three village groups

belonged mostly to the Senufo ethnic group.

During the eight monitoring periods, 38 139 blood

samples were taken. Their distribution according to sub-

jects clinical status and agroecosystems is shown in

Figure 1. Nine fever episodes (from the three farming

systems) without thick smears were excluded from the

study. Each fever syndrome corresponds to one illness

episode per person and per survey.

Irrespective of the farming system, population partici-

pation in the study was high. In fact, some 79% of

R1 and R2, and 77% of R0 populations took part in

at least seven of the eight monitoring periods. An average

of six blood samples per person was taken from 75% of

R1 and R2, and 70% of R0 populations. Each person

of R0, R1 and R2 was visited at home on 27 days (9) on

average over the 40 active detection days planned in the

protocol.

Parasitological indexes of asymptomatic subjects

observed during CSS

Table 2 shows a considerable predominance of P. falcipa-

rum over P. malariae and P. ovale in the asymptomatic

infections in all the agroecosystems. The plasmodia distri-

bution was comparable across the three agroecosystems:

P. falciparum, 99.3%; P. malariae, 5.17.9%; and

P. ovale, 0.51.5% according to agroecosystems. Annual

average prevalence of P. malariae was 9 years), seasons and agroecosys-

tems. The mean annual prevalence of P. falciparum

infections ranged from 65% in R2 to 72% in R1 and R0.

Everywhere, more than 80% of children from 2 to 9 years

old were parasite-positive, with the highest percentage in

the age group 24 years. About 50% of adults aged 40 and

above were still infected. The mean annual gametocyte

rates reached about 7% everywhere. As observed in other

endemic areas, the three parasite indexes (trophozoite and

gametocyte rates and parasite density) were higher in

children than adults. Multivariate analysis showed that

P. falciparum asexual stages prevalence and parasite

densities decreased with age according to agroecosystems

(P < 0.001) (Table 4). The three parasite indexes were

higher in the rainy season than in the dry season in the

three agroecosystems. Seasonal variations in P. falciparum

asexual stages prevalence and parasite density differed

between agroecosystems (P < 0.001) (Table 5). This

increase in parasite densities during the rainy season was

less pronounced or absent among older children and

adults. With the onset of rains, parasitaemia increased

earlier in R0 than in R1 and R2 and with the onset of

the dry season, parasitaemia dropped faster in R0 and R1

than in R2.

Table 1 Distribution of population samples according to farm-

ing systems (R0, no rice cultivation; R1, single rice cropping;

R2, double rice cropping)

Age group

(year)

R0

n (%)R1

n (%)R2

n (%)

01 164 (8) 144 (7) 164 (8)

24 246 (12) 185 (9) 164 (8)59 411 (20) 370 (18) 308 (15)

1019 392 (19) 514 (25) 473 (23)

2039 411 (20) 411 (20) 411 (20)40 221 (11) 431 (21) 555 (27)

Total 2054 (100) 2055 (100) 2075 (100)

Exclusion of 705 blood samples obtained twice from the same personduring the same monitoring period

37 434 blood samples

38 139 blood samples

36 387 in asymptomaticsubjects observed during thecross sectional surveys

1047 in febrile subjects foundby the active case detectionmethod

11 951 inR0

12 306 inR1

12 130 inR2

355 inR0

344 inR1

348 inR2

Figure 1 Distribution of blood samples according to clinicalstatus and farming systems (R0, no rice cultivation; R1, single

rice cropping; R2, double rice cropping).




Clinical malaria incidence observed by ACD method

We considered only one fever episode per patient and

survey. If two or more fever episodes were observed during

two or more different monitoring periods in the same

patient, each fever episode per survey was taken in

account. Figure 2 shows the characteristics of the 1047

patients detected in the three agroecosystems. Among these

patients, there were 212 (nearly 20%) parasite-negative

subjects, 831 subjects with P. falciparum single or mixed

infection and four subjects with P. malariae or P. ovale

single infection. The distribution of Plasmodium species in

the patients according to the agroecosystems is reported in

Table 2. The three P. malariae single infections showed a

density

five in R0. Between age 2 and 9 years, they had one to two

malarial attacks per year. From 10 years on, villagers had

trophozoites per microlitre, respectively, for people aged

04, 59, and 10 years and above. The sensitivity of

malaria case definition varied between 0.7 and 0.9 whereas

the specificity was equal to 0.8, in each of the three

agroecosystems.

Antimalarial drug consumption was very low in the

three agroecosystems. No traces of sulphamide, amodia-

quine and quinine were found in urine. Chloroquine

and/or its metabolites were detected in 1.7% of R1

(2/172) and R0 (4/236) samples, and 4.7% of R2 (7/149)

samples. This higher rate in R2 was due to the fact that

20% of the samples (5/24) of Kohotieri village were

positive.

Discussion

The parasitological indices showed that in the three

agroecosystems malaria is highly endemic. Even if the

mean annual prevalence was 70% among infants, para-sitaemia slowly reduced between 2- and 5-year olds, and at

least one of two adults was parasite-positive. This level of

Table 6 Annual incidence density of fever and malarial attack (found by the active case detection method) according to age groups and

farming systems (R0, no rice cultivation; R1, single rice cropping; R2, double rice cropping)

Age group(years)

Observations Fever Malaria fever

Malaria fever in the standard

population of 1000 persons

n Person-day n

Incidence

per person-

year

Attributable

fraction*

Incidence

per person-

year

Population(%)

Incidence

per year

(95% CI)

R0 01 1116 4688 112 8.7 62.2 4.8 7.4 356 (129766)24 1687 7157 69 3.5 45 2.3 9.8 224 (70467)

59 2870 11 407 54 1.7 15.7 0.5 17.5 88 (18225)

1019 2667 10 009 38 1.4 15.7 0.6 21.4 123 (30283)

2039 2968 11 248 49 1.6 10.6 0.3 19.9 69 (12204)40 2997 11 754 33 1 6.6 0.2 24 49 (5172)Total 14 305 56 263 355 2.3 155.8 1 100 909 (7861045)

R1 01 1065 4549 97 7.8 36.8 3 7.4 217 (46564)

24 1356 5640 52 3.4 17.7 1.1 9.8 118 (11358)59 2516 9697 66 2.5 21.8 0.8 17.5 144 (41318)

1019 3479 12 867 45 1.3 6 0.2 21.4 37 (1135)

2039 2868 10 746 38 1.3 4.3 0.1 19.9 29 (0133)

40 3257 13 018 46 1.3 3 0.1 24 20 (0110)Total 14 541 56 517 344 2.2 89.6 0.6 100 559 (464668)

R2 01 970 4172 73 6.4 34.6 3 7.4 223 (50615)

24 1132 4867 71 5.3 40.6 3 9.8 297 (81634)59 2113 8064 65 2.9 26 1.2 17.5 210 (75445)

1019 3026 11 055 47 1.6 10.4 0.3 21.4 74 (12208)

2039 2703 9964 41 1.5 3.6 0.1 19.9 26 (0143)

40 4028 15 248 51 1.2 2.2 0.1 24 12 (094)Total 13 972 53 370 348 2.4 117.4 0.8 100 842 (720977)

* Fever fraction attributable to malaria was estimated by logistic regression model.

Ratio of the total study population in the age group to the study population as a whole.

R0

0200400600800

1000

0246810

R1

0200400600800

1000

0246810

R2

Months of survey

0200400600800

1000

D-96

J- F M A M J J A S O N D J- F97 98

0246810

Mal

aria

atta

cks/

1000

child

-day

Infe

ctive

bite

s/10

00m

an-n

ight

Infe

ctive

bite

s/10

00m

an-n

ight

Infe

ctive

bite

s/10

00m

an-n

ight

Mal

aria

atta

cks/

1000

child

-day

Mal

aria

atta

cks/

1000

child

-day

Figure 4 Incidence density of malaria fevers (point) in children

09 years old (found by active case detection method) as a con-sequence of the entomological inoculation rate (bar) in the three

farming systems (R0, no rice cultivation; R1, single rice cropping;

R2, double rice cropping).




high endemicity is compatible with the perennial trans-

mission with pronounced seasonal peaks observed in the

three agroecosystems. The mean annual inoculation rate

was similar in all of the three agroecosystems, with,

respectively, 158, 139 and 155 infective bites per person

per year, in R0, R1 and R2 (Dossou-Yovo et al.,

unpublished data).

The clinical study showed that, irrespective of the

system, inhabitants experience on average two fever

attacks per year. However, the age-standardized annual

malaria incidence was 0.9 malarial attacks per person in

R0, 0.6 in R1 and 0.8 in R2. It is mainly P. falciparum that

causes malaria fever episodes. If it is assumed that

pyrogenic parasitic densities are similar for all plasmodia

species among people of a given age in highly endemic

conditions (Trape et al. 1994), only one malarial attack

with a P. ovale single high parasitic infection was detected.

The three subjects with a P. malariae single infection had a

very low parasite density, apparently not compatible with

diagnosis of malarial attack.

To quantify malaria morbidity, we used the method of

estimation of fever fractions attributable to malaria. This

method can be applied even if distribution of parasite

infection on asymptomatic subjects includes a number of

highly infected individuals (Smith et al. 1994). In our

study, 8% of asymptomatic children had an infection

above 5000 P. falciparum trophozoites per microlitre,

whereas this was the case for 37% of the sick ones. Eight

per cent of healthy subjects aged 10 years or older had

more than 500 parasites/ll whereas this was the case for16% of sick subjects of the same age group.

These high asymptomatic parasitaemias observed are

attributable to recent malaria cases which occurred before

the monitoring period. Malaria fevers are short especially

in adults (Rogier et al. 1999), and they may not all have

been reported. Finally, self-medication is common. Indeed

in the Korhogo region, traditional medicine, most often

plants, is systematically used in the first instance to treat

febrile people (De Plaen et al., personal communication).

This may have been effective against fever but not against

parasites. Smith et al. (1994) observed that parasite

distribution in non-feverish subjects is different, depending

on place of detection in the village or in the health centre.

Also they attributed high asymptomatic parasitaemia

observed in the village to recent cases of malaria.

The three agroecosystems present a distinct epidemio-

logical behaviour concerning immunity acquisition in

children from 0 to 9 years old. In this age group, annual

parasite prevalence and parasitaemia in asymptomatic

subjects were slightly higher in R0 than in R1 and R2. The

annual incidence of clinical malaria reached on average

two malarial attacks per child in R0 and R2, whereas

children in R1 suffered less from malaria, with 1.4 episodes

per year. However, reduction of malaria risk between 04

and 59 age groups seemed more important in R0 (6.6

factor) than in R1 and R2 (2.5 factor). Observations might

suggest that, between 0 and 4 years, children in R0

encounter a higher malaria risk than those in R1 and R2.

The values of risk reduction fall into the range observed

between the same age groups in other studies (Snow et al.

1999). Plasmodium malariae and P. ovale were more

frequently found in R0 than in R1 and R2, especially in the

04 age group. However, their prevalence did not differ

with the season. As Anopheles funestus was more fre-

quently captured in R0 than in R1 and R2, P. malariae

could be preferably transmitted by this vector (Boudin

et al. 1991). However, our observations do not allow the

verification of this hypothesis.

The three agroecosystems also present a distinct epide-

miological seasonal pattern. Generally, in all three,

asymptomatic infections were stronger and more frequent

during the rainy season than in the dry season, especially in

children up to 9 years old. There were also more malarial

attacks during the rainy season. However, in R1 the

increase of parasite load in sick children at the beginning of

the rainy season was lower than in R0 and R2 and it

remained low during the rest of the rainy season. Malarial

attacks were also less frequent, although the transmission

rate was the same as in the two other agroecosystems.

Neither chloroquine consumption, which was very low, nor

protection with mosquito nets, which were used only by

about 4% of the population in the three agroecosystems,

can explain these findings. The use of fumigation, mosquito

coils or aerosol insecticides was more frequently reported in

R1 than in R2 and R0 (M. Audibert, personal communi-

cation). According to Snow et al. (1998), their use does not

protect against mild but rather against severe malaria

disease. Moreover the R1 families were richer than those of

R2 and most of R0 (Audibert et al. 2003). Further inves-

tigations are needed to determine how the family richness

might have an effect on the reduced incidence in R1.

In R2, with irrigated rice cultivation, malarial attacks

persisted for a short period in the beginning of the dry

season before decreasing. Conversely, in R0 and R1, they

reduced abruptly at the end of the rains. The temporarily

maintained level of malaria morbidity, which closely

coincided with the prolongation of transmission period in

R2, was almost non-existent in R0 and R1. The prolong-

ation of intense hostparasite contact in R2 resulted in a

smaller increase in malaria risk in R2 than in R0 and R1 in

the rainy season.

Our findings are somewhat different from the observa-

tions made in other irrigated rice cultivation zones in West

Africa. In an irrigated zone of The Gambia (Lindsay et al.




1991) malaria fever incidence, highest during the rainy

season, persisted during the first week of the dry season

before decreasing. In Burkina Faso in dry savannah

(Boudin et al. 1992), plasmodia infection incidence became

maximal at the beginning of the dry season and then

decreased in villages with irrigated rice cultivation,

whereas incidence was highest during the rainy season in

the villages without rice cultivation. In Mali (Sissoko et al.,

unpublished data), malaria fever incidence was fairly

constant over the seasons at a low level in an irrigated zone

whereas incidence was low during the dry season and high

at the end of the rainy season in a non-irrigated zone.

It is clear that in northern Cote dIvoire savannah, the

double cropping rice system extends malaria risk during a

short period, in the beginning of the dry season. It does not

modify annual malaria incidence in the developed lowlands

zone, which is comparable with the uncultivated lowlands

zone, with the same annual transmission rate. These results

confirm that in a stable malaria zone, rice cultivation does

not significantly affect malaria pressure, contrary to what

may occur in an unstable malaria zone (Carnevale et al.

1999).

In conclusion, in the savannah region of northern Cote

dIvoire, lowland rice cultivation does not significantly

influence malaria risk, but socio-economic and cultural

factors might reduce malaria pressure. Because of the

large scale study and the methodology focused on

malaria, estimates in the context of farming systems rather

than in single villages, the data presented contribute to a

better knowledge of the malaria risk related to rice

cultivation.

Acknowledgements

This study was undertaken within the framework of the

WARDA/WHO-PEEM/IDRC/DANIDA/Government of

Norway Health Research Consortium on the Association

between irrigated Rice Ecosystems and Vector-Borne

Diseases in West Africa. The Consortium received techni-

cal assistance from the International Development

Research Centre (IDRC), Ottawa, Canada and financial

support from the International Development Research

Centre (IDRC), Ottawa, Canada, the Danish International

Development Agency (DANIDA) and the Royal Govern-

ment of Norway.

We thank the Korhogo District Health Officer,

Dr Richard Kohou and his deputy, Dr Felix Bledi, as well

as Dr Aboudramane Konate, Head of Niakara Hospital.

We also thank the village chiefs and population for their

warm welcome during each of our visits. Finally, we are

grateful to the team of nurses, health workers and

microscopists who made this study possible. The principal

investigator thanks the French Institut de Recherchespour le Developpement, especially Dr F. Riviere andDr B. Philippon, for their support.

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Authors

Elena Akodo and Thomas M. Teuscher, West Africa Rice Development Association, Bouake, Cote dIvoire. Tel.: +225 3163 8983;

E-mail: [email protected]

Marie C. Henry (corresponding author), I. Nzeyimana, S. B. Assi, J. Dossou-Yovo and P. Carnevale, Institut P. Richet, BP 1500,

Bouake 01, Cote dIvoire. Tel.: +225 31 63 37 46; E-mail: [email protected]; [email protected]; [email protected];

[email protected]; [email protected]

M. Audibert and J. Mathonnat, CERDI, 65 Boulevard F. Mitterand, F-63000, Clermont-Ferrand. E-mail: [email protected]

clermont1.fr; [email protected]

C. Rogier and A. Keundjian, BP46, Parc du Pharo, 13998 Marseille-Armees, France. Tel.: +33 491 15 01 50/52;

E-mail: [email protected]; [email protected]




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