Am. J. Trop. Med. Hyg., 71(4), 2004, pp. 451-456
Copyright © 2004 by The American Society of Tropical Medicine and Hygiene
PHYSIOGRAPHIC AND ENTOMOLOGIC RISK FACTORS OF MALARIA IN ASSAM, INDIA
VAS DEV,
SOBHAN PHOOKAN,
VINOD P. SHARMA, AND
SURAJ P. ANAND
Malaria Research Centre (Indian Council of Medical Research), Sonapur, Assam, India; Malaria Research Centre (Indian Council of Medical Research), Delhi, India; DevOps (Pfizer)–India, Jogeshwari (W), Mumbai, India
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ABSTRACT
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Fever surveys were conducted in several districts of the Indian state of Assam to ascertain the prevalence of malaria in relation to vector abundance, entomologic inoculation rates (EIRs), and geographic location of human settlements. Anopheles minimus were incriminated, but their relative abundance and biting rates varied among districts, and no significant correlation was observed between these two indicators (r = 0.43, P = 0.34). Plasmodium falciparum was the predominant parasite species except in two districts where P. vivax was the majority parasite. The EIRs per person/night were 0.46–0.71 in P. falciparum-predominant areas and 0.12 in the district where P. vivax predominated. The correlation of percentage of fever cases positive for malaria infection in each district with the corresponding EIR was not significant (r = 0.6, P = 0.21). Malaria cases were detected in all months of the year but peaked during May–June, which corresponded to the months of heavy rainfall. These were also the months with highest incidence of infection with P. falciparum. Malaria cases were observed in all age groups of both sexes, and there was clustering of cases in villages near the vector-breeding habitat (perennial seepage streams), and foothill villages. However, malaria incidences were consistently lower in villages within 5 km of the nearest health care facility, which were in town areas. The data presented are indicative of low-to-moderate levels of malaria transmission by An. minimus, and would be of value for developing future intervention strategies.
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INTRODUCTION
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Assam is the most populous and second largest of the seven states in the northeastern region of India. Malaria is endemic in the region, and Assam contributes more than 5% of the total cases recorded in the country annually. Malaria transmission is perennial and under the influence of several vector species including Anopheles minimus (the perennial species), An. dirus (the monsoon species), and An. fluviatilis (the winter species). Plasmodium falciparum accounts for 58–68% of the cases and the remainder are due to P. vivax.1,2 Almost all districts of Assam report malaria attributable morbidity and mortality annually, and are vulnerable to focal outbreaks of the disease. Every death reported to have been due to malaria was confirmed to have been associated with a P. falciparum infection. Chloroquine-resistant malaria is widespread in the state, and decreased sensitivity to other anti-malarials has been documented.3–5 Malaria is spreading to new areas where there is enhanced morbidity and mortality.6 One hundred three of 156 primary health centers in Assam are identified as being high risk for malaria based on the selected epidemiologic criteria, and nearly 65% of the total population of the state (26.6 million) is estimated to be living in high-risk areas. Districts bordering other states in the northeastern region or countries including Bhutan and Bangladesh are at a greater risk of focal outbreaks due to the inadequate health infrastructure and lack of coordinated vector control operations. The disease is unevenly distributed across the state and associated with varying intensity of malaria transmission and risk factors.
The objective of the present investigation was to ascertain the incidence of malaria, and to assess the relative risk in relation to distance from vector breeding habitat and health care facilities and the geographic location of human settlements. The study also aimed to assess the association between other possible factors such as vector abundance, biting activity, and entomologic inoculation rates (EIRs) thought to be contributing towards the overall risk. The data reported will allow the decision makers to develop newer strategies in countering malaria, and help in designing studies on vaccine evaluation and define endpoints for effective control.
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MATERIALS AND METHODS
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Study area.
The investigations were conducted on the north and south banks of the Brahmaputra River in the Assam valley. The populations in these areas are predominantly tribal aborigines rich in their cultural heritage, but living in poverty. Many villages are located in the foothills/forest fringe amid paddy fields, and have poor access to primary health care. There are several perennial seepage water streams/channels associated with rice fields, and are natural sources of irrigation. Shifting cultivation is common in many foothill/hilltop villages. Most areas in the state have heavy rainfall, ranging from 2 to 3 meters, and floods occur annually. Maximum precipitation associated with the monsoons occurs from May to September, and is preceded by pre-monsoon showers in March and April. The relative humidity varies from 60% to 85%. Temperatures range from 10°C to 26°C in winter (November–February) and from 23°C to 33°C throughout rest of the year. The fauna and flora is rich and evergreen forest covers more than 40% of the total land area. Tea is the major cash crop; other occupations include paddy cultivation, handlooms, and forest produce. Verbal consent was obtained from the participating subjects, and the study was reviewed and approved by the Ethics Committee of the Malaria Research Center.
Entomologic investigations.
Daytime resting catches were made in human dwellings (indoors) between 5:00 AM and 7:00 AM by experienced insect collectors. Mosquito adults resting on the walls, hanging clothes, etc., in houses were collected by suction tube aided by torchlight. For night biting catches, mosquito adults landing on exposed body parts of adult human baits were collected between 6:00 PM and 5:00 AM inside the house. Mosquito collections were made throughout the night by two teams of two insect collectors each, and these were rotated on an hourly basis. All anopheline species thus collected were identified to the species level, and those with a high anthropophilic index were dissected for their salivary glands in a 0.9% saline solution for detection of sporozoites. These included An. aconitus (30), An. annularis (293), An. culicifacies (46), An. dirus (14), An. minimus (332), An. nivipes (22), and An. varuna (1,035). All the species dissected were sporozoite negative except for An. minimus. Having incriminated An. minimus as the vector in Kamrup district, data were collected from other malaria-endemic districts on their relative abundance in day resting populations, sporozoite infectivity, and the biting rates per person/night. The EIR was calculated as the product of the human mosquito-biting rate and the proportion of mosquitoes carrying sporozoites in their salivary glands. The entomologic procedures and other topographic features are detailed elsewhere.1
Parasitologic investigations.
For detection of malaria cases, active fever surveillance was conducted from 1988 to 1992 at weekly intervals in 50 villages (population ~22,500) of the Sonapur Primary Health Center (Kamrup District). Data were analyzed on monthly distribution of cases, and parasite species composition in relation to age, sex, and ecology. For all other districts, point prevalence surveys were conducted from 1991 to 2000 to determine malaria positivity in clinical cases, and parasite species composition in relation to entomologic indicators. These included districts of Karbi Anglong, Kokrajhar, Sonitpur, Darrang, Nagaon, Golaghat, Lakhimpur, Goalpara, Morigaon, and Nalbari. In these districts, malaria clinics were established for passive surveillance. A finger prick sample of blood was collected from those presenting with fever (clinical cases), and stained with Singh and Bhattarcharya (JSB) stain.7 The JSB stain is commonly used in the malaria control program in India, and is less time-consuming than the Giemsa staining procedure. Both thick and thin blood smears were examined under an oil immersion (x 100) objective for parasite positivity and species identification, respectively. A total of 100 microscopic fields were scanned before declaring a slide negative. All positive slides and 20% of those negative were cross-examined by the senior technician for accurate species identification of the malarial parasite. Malaria-positive cases were given anti-malarials according to the national drug policy. Most point prevalence surveys were conducted in the wet season (May to November).
Statistical analyses.
Poisson (log-linear) regression was performed based on malaria incidence cases in three population years (1990–1992) to model annual parasitic incidence (API) rates using the GENMOD procedure in SAS system version 8.2 (SAS, Cary, NC). Logarithm of incidence rate was modeled as a linear function of the risk factor. Type 3 analysis was performed to test the significance of the main effects. A dispersion parameter was set to deviance/degrees of freedom to account for over-dispersion in the data. Scaled deviance was used as the criteria for assessing goodness of fit. Maximum likelihood method was used to estimate the parameters in the model. Univariate analysis was performed to assess the significance of individual risk factors. Relative risk for API rates with respect to the reference category was provided with Wald 95% confidence limits (by taking exponentiated model values) and the corresponding P values. Multivariate analysis with backward elimination method was used to develop the most parsimonious model for the risk factors. Spearman’s rank correlation coefficient values were worked out where indicated. A chi-square test for independence was performed to check for any significant differences in the proportions of malaria cases across different age groups and sexes. Stratified analysis was done to avoid confounding effect between these two factors.
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RESULTS
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Mosquito biting rates, abundance, and infectivity.
In the human bait catches, 17 mosquito species were collected (Table 1
). Taken together, An. minimus were most abundant; others included An. aconitus, An. nivipes, An. varuna, An. splendidus, An. kochi, and An. annularis in order of their decreasing biting rates. Anopheles minimus were collected in all months, with the highest biting rates during May to July. Anopheles aconitus were collected in all months except November; its peak biting activity was observed in August and exceeded that of all other species. The biting rate of An. nivipes was the highest of all species during the months of September and October. Anopheles varuna were also collected throughout the study period, but the biting rate varied from 0.25 to 5.25, with the maximum in August. For An. splendidus, An. kochi, and An. annularis, peak biting was recorded in June. For all other species, cumulative biting rates were < 1 per person/night. Overall, the biting rate was highest in June and lowest in November.
The data on prevalence of An. minimus, mosquito biting rates, sporozoite infectivity, and corresponding EIR in the districts surveyed are shown in Table 2. Anopheles minimus were collected in all districts; however, their relative abundance and mosquito biting rates varied between the districts. For the seven districts for which data exist, there was no significant correlation between daytime resting collections and biting rates of An. minimus (r = 0.43, P = 0.34). The highest biting rates were recorded in the districts of Morigaon and Darrang. Sporozoites were found in An. minimus in all districts except Lakhimpur, and the sporozoite infection rate varied from 0.010 to 0.065. The estimates of EIRs ranged from 0.12 to 0.71. It was the lowest in Golaghat district where there were mainly P. vivax cases, whereas these values were much higher in areas where P. falciparum was predominant. For the six districts for which these data exist, the correlation of percentage of clinical cases positive for malaria with EIR was not significant (r = 0.6, P = 0.21). However, it was interesting to observe that P. falciparum cases seem to increase significantly with the EIR (r = 0.83, P = 0.04) in contrast to P. vivax cases, which decreased significantly (r = –0.94, P = 0.005) with the EIR.
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TABLE 2 Relative abundance of Anopheles minimus, sporozoite infectivity, mosquito biting and entomologic inoculation rates (EIRs), and prevalence of malaria in endemic districts of Assam, India
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Seasonal prevalence of malaria and risk factors.
In the point prevalence study, all districts investigated were observed to be endemic for malaria, but the positivity rate and composition of parasite species varied between districts (Table 2
). Plasmodium falciparum was the predominant infection in most districts. In these districts, 17–48% of the clinical cases positive for malaria were due to P. falciparum; the remaining were P. vivax infections. However, in districts of Nagaon and Golaghat located south of Brahmaputra River, P. vivax was the predominant parasite and proportions of those positive for the species far exceeded those positive for P. falciparum.
Data on monthly distribution of malaria cases and species parasite composition are shown in Table 3. In active fever surveys, malaria cases were detected in all months of the year, but peaked when rains were the heaviest (May–June). Anopheles minimus biting rates reached a sharp peak in May and June (Table 1), the months of heaviest rains. These were also the months of highest incidence of infection with P. falciparum, but the incidence remained high for several months after An. minimus biting activity had decreased, presumably because of variable times between occurrence of infective bites and patients presenting with symptoms. The correlation between these parameters for the months of April to November was not significant (r = 0.61, P = 0.11). This may be due to the different shape of the peak for An. minimus biting activity (Table 1), and to the monthly parasite incidence (Table 3) due to a time lag associated with extrinsic incubation period and the exo-erythrocytic period.
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TABLE 3 Monthly distribution of malaria cases and species parasite composition in the Sonapur Primary Health Center, Kamrup District, Assam, India*
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Distribution of malaria incidence by age group, sex, and location.
Malaria cases were observed in all age groups of both sexes (Table 4). There was no significant difference in proportions of positive cases (P = 0.144) between the two sexes across age groups except in those 5–15 years old, in whom the proportion was significantly lower for females (P = 0.046). Proportions of cases positive for malaria were significantly different (P < 0.0001) across age groups for both the sexes. In males, there was an increasing trend in the proportion of malaria cases with age (lower in those < 1 years of age compared with those 1–4 and 5–15 years old), but the proportions for those > 15 years old were significantly smaller (P < 0.0001) than those for all age groups combined (0–15 years old). However, in females after an increase in the proportion of malaria cases with age (lower in those < 1 year of age compared with those 1–4 years old), there was a decrease with the combined proportion for the age group (> 5 years old) that was significantly smaller (P < 0.0001) than when the first two groups (0–5 years old) were taken together. Similar trends were observed for the data combined for both the sexes, with a significantly higher concentration of malaria cases in those 1–15 years old compared with those < 1 year of age or those >15 years old (P < 0.0001).
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TABLE 4 Distribution of malaria cases in relation to age and sex in endemic villages in the Sonapur Primary Health Center, Kamrup District, Assam, India*
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Geographic locations of human settlements appeared to be significant factors for the acquisition of malarial infection (Table 5). Using the logarithm of the API rate as a dependent variable, statistical analyses showed that the distance from the breeding habitat was a significant epidemiologic factor. Villages located nearer (
1 km) to the breeding habitat (i.e., seepage streams) of the vector species had significantly higher API rates, i.e., mean numbers of cases per thousand of population/year (relative risk = 10.46, P < 0.0001) than those located farther (> 1 km) from the breeding source. Similarly, cultivators living in foothill villages (practicing shifting cultivation) had significantly higher API rates than villagers in plain areas (relative risk = 3.63, P < 0.0001). Furthermore, malaria incidence was consistently higher in villages more than 5 km from the nearest health care facility than those located nearer (relative risk = 3, P = 0.0013). The multivariate analysis of risk factors (final model selected using backward elimination procedure) indicated that among the risk factors investigated, distance from breeding habitat and geographic location of human settlements were the most significant risk factors in order of importance (with both the P values <0.0001 in the final model), and the risk due to distance from health care facility was confounded with the latter. The corresponding adjusted relative risks and the 95% confidence intervals were 7.28, 3.23–16.41 and 2.22, 1.49–3.32, respectively.
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TABLE 5 Distribution of malaria cases in relation to risk factors specific to the Sonapur Primary Health Center, Kamrup District, Assam, India*
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DISCUSSION
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Malaria is a major public health concern in the northeastern states of India. For its control, the mapping of malaria risk across the state on the larger area will assist in decision-making on the location and deployment of health care services and prioritizing of intervention strategies. From the presented data on entomologic aspects, it is reaffirmed that An. minimus is the major vector in the areas investigated. It was incriminated in most districts by detection of sporozoites in salivary glands, but species of the sporozoites were not ascertained. However, this seemed to be an efficient vector for transmission of P. falciparum malaria, as shown by its high sporozoite infection rates, particularly in P. falciparum-predominant districts (Table 2). Among other vector species, An. dirus has been incriminated in other parts of the state, but its role in the present study areas could not be substantiated. The population densities of An. dirus are believed to be dwindling because of widespread deforestation associated with human population increases, and increased acreages under paddy cultivation. Anopheles fluviatilis were not observed in the present study, but seasonal sporozoite infections have been documented during the winter months.1
There was no significant correlation between density of indoor day resting populations of An. minimus and the human biting rate. This could be attributed to local factors related to variable rainfall and human activities in different years. However, these data do suggest the existence of sibling species of An. minimus in range of its distribution in Assam, as has been documented in Thailand.8 Not surprisingly, the mosquito biting rate of An. minimus and associated EIRs were heterogeneous among districts. Overall, EIR values were < 1 per person/night and ranged from 0.12 to 0.71; these are indicative of low-to-moderate transmission intensities in this region when compared with lowland tropical Africa.9–13 Nevertheless, there is an intrinsic bias in EIR values calculated based on the adult human biting rate; the real values are likely to be much lower should these be based on the infant conversion rate, as applied in Africa (Carter R, unpublished data). However, the present study is suggestive of an association (though not a significant one) between EIR and parasite rates, as has been observed in tropical Africa for An. funestus, which is a very similar species to An. minimus.10,12,13
Based on the monthly distribution of malaria cases, it is apparent that the area is co-endemic for P. falciparum and P. vivax, and the transmission intensities between months are variable. The increase in P. falciparum infections during the monsoons could be attributed to an increase in critical temperatures for sporogonic development of the parasite in the vector host.14,15 All age groups of both sexes were prone to malaria infection, unlike the situation in lowland Africa where immunity builds up readily to an important extent as a result of repeated exposure during childhood regardless of the inoculation rates.16,17 However, the concentration of malaria cases in children (1–15 years old) compared with infants (<1 year of age) and older age groups (> 15 years old) is suggestive of maternal immunity and a higher degree of care during infancy, while some increases in immunity in older age groups is due to repeated exposures to malarial attacks.
There appeared to be clustering of malaria cases in certain localities in relation to physiographic locales. Malaria incidence was the highest in villages located near seepage water streams (< 1 km), which is the preferred breeding habitat of An. minimus,18 as well as in the foothill villages, which are associated with shifting cultivation and forest-related activities. The distance estimated to be flight range of An. minimus, and supposedly the mosquito actively searches the host within this range. Similarly, the risk of contracting malarial infection was consistently higher in the foothills compared with the plains. The effect of malarial infection due to distance from health care facility was confounded with the risk due to geographic location. A possible reason for this confounding effect is that most of the health care facilities are concentrated in the plains; thus, it is difficult to separate the individual effects of these two risk factors. Nevertheless, the risk of malaria was shown to be higher in the peripheral areas more than 5 km from a health care facility. This could be attributed to prevailing malariogenic conditions/entomologic activity, as well as to the low socioeconomic status of population groups in the periphery. In town areas (< 5 km from a health care facility), housing conditions are much better, which limits access to vector mosquitoes, and the people are more aware of the disease and its prevention and have better access to the primary health care. Such associations have been observed in other agro-climatic zones under the influence of different vector species in tropical Africa, Southeast Asia, and other neighboring states of the northeastern India.9,19–22 The risk for malaria has been linked with poverty and environmental degradation, and it calls for political commitment to strengthen the health services, particularly in the periphery, in keeping with global agenda to roll back malaria.23–25 Population groups in these areas, besides having little awareness on the disease, are often devoid of primary care needs due to recurrent floods.
Consistent with the outcome of the present investigation, in areas with low-to-moderate EIR, well-managed campaigns with appropriate tools, especially insecticide-treated nets, would result in significant reduction in case incidences, and this is seemingly achievable.26–28 Geographic information system-based approaches, when combined with traditional methods of data collection, would permit more accurate targeting of interventions where these are needed most and save costs. In conclusion, this study provides information on characteristics of malaria transmission and associated risk factors specific to northeastern India, and would be of practical value for health planners and policy makers in evaluating malaria vaccines trials and other newer approaches for malaria control in this part of the world.29,30
Received November 5, 2003.
Accepted for publication March 29, 2004.
Acknowledgments: We are grateful to Dr. C. F. Curtis (London School of Hygiene and Tropical Medicine), Dr. R. Carter (University of Edinburgh), and the anonymous reviewers for their comments and advice on the manuscript. Thanks are also given to Dr. C. Lele (Pfizer, Ltd.) for statistical input and to the Assam Branch Indian Tea Association and State Health Directorate (Government of Assam) for logistics support in remote areas of the state. Technical assistance of the project staffs is gratefully acknowledged. Meteorologic data were obtained from the Regional Meteorological Centre, Guwahati (Assam). This study was presented at the Joint Malaria and Spring Meeting of the British Society of Parasitology held in Manchester (April 6–9, 2003) through the grant to Vas Dev by the Director General, Indian Council of Medical Research, New Delhi.
Authors’ addresses: Vas Dev and Sobhan Phookan, Malaria Research Centre (Indian Council of Medical Research), PO Sonapur, Kamrup, Assam 782 402, India, E-mail: mrcassam{at}hotmail.com. Vinod P. Sharma, Malaria Research Centre (Indian Council of Medical Research), 22 Sham Nath Marg, Delhi 110 054, India, E-mail: v_p_sharma{at}hotmail.com. Suraj P. Anand, Biometrics, DevOps-India (Pfizer Global R&D) 5, Patel Estate, S.V. Road, Jogeshwari (W), Mumbai 400 102, India, E-mail: surajanand{at}rediffmail.com.
Reprint requests: Vas Dev, Malaria Research Centre, PO Sonapur, Kamrup, Assam 782 402, India.
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ABSTRACT
INTRODUCTION
