Sri Lanka malaria maps

Eliminating malaria in conflict zones: public health strategies developed in the Sri Lanka Civil War

Despite the 26-year long civil war, Sri Lanka was declared malaria-free by WHO in 2016. This achievement was the result of nearly 30 years of elimination efforts following the last significant resurgence of malaria cases in Sri Lanka. The resurgence occurred in 1986–1987, when about 600 000 cases of malaria were detected. Obstacles to these efforts included a lack of healthcare workers in conflict zones, a disruption of vector control efforts, gaps in the medication supply chain, and rising malaria cases among the displaced population.

This article seeks to describe the four strategies deployed in Sri Lanka to mitigate the aforementioned obstacles to ultimately achieve malaria elimination. The first approach was the support for disease elimination by the government of Sri Lanka and the Liberation Tamil Tigers of Elam. The second strategy was the balance of centralised leadership of the federal government and the decentralised programme operation at the regional level. The third strategy was the engagement of non-governmental stakeholders to fill in gaps left by the conflict to continue the elimination efforts. The last strategy is the ongoing efforts by the government, military and non-profit organisations to prevent the reintroduction of malaria.

The lessons learnt from Sri Lanka have important implications for malaria-endemic nations that are in conflict such as Ethiopia, Afghanistan, Yemen and Somalia. To accomplish the World Health Assembly goal of reducing the global incidence and mortality of malaria by 90% by 2030, significant efforts are required to lessen the disease burden in conflict zones. In addition to the direct impacts of conflict on population health, conflicts may lead to increased risk of spread of malaria, both within a country and consequently, abroad.

The key role of socio-demographic and socio-environmental factors in urban malaria occurrence and control - An illustration using the city of Yaoundé

Cities in developing countries are experiencing an unprecedented population growth that illustrates a demographic transition and a shift towards modernization with consequences on their epidemiological profiles. However, this change is characterized by an important rural-to-urban social and cultural transfer that can bias the expected epidemiological transition; at the same time, this transfer renders the understanding of the occurrence of communicable diseases more complex than it appears. Urban malaria occurrence was modeled for the city of Yaoundé in Cameroon. Retrospective interviews were conducted to describe a variety of epidemiological, social and environmental variables at the household level. Various ecological variables originating from remote sensing data were also integrated. Multivariate multilevel negative binomial analyses were developed to evaluate the distinct contributions of explanatory social and ecological variables. Spatial models based on the level of urbanity were implemented to understand the intelligence of urban malaria as characterized by those variables. The results showed an overall higher statistical importance of socio-environmental variables, particularly those describing rural origin socio-cultural features in terms of non-conventional housing types and urban agriculture (UA). The spatial patterns of the urban malaria occurrences displayed a complex combination of population density gradients and socio-environmental factors, illustrating the importance of conventional urban features over rural/non-conventional features in reducing the occurrence of urban malaria.

Prioritizing areas for malaria control using geographical information system in Sonitpur district, Assam, India

OBJECTIVE

To identify the malaria hot spots at health subcentre level in an endemic district using a geographical information system (GIS). The results will be useful for rapid retrieval of malaria information, and to prioritize malaria control efforts in identified hot spots.

STUDY DESIGN

Extraction, analysis and synthesis of relevant data.

METHODS

Malaria epidemiological data from 2006 to 2009 were analysed to determine the annual parasitic index, slide positivity rate, annual blood examination rate and Plasmodium falciparum percentage for each health subcentre in the district. Maps were produced using GIS, and integrated to identify the malaria hotspots.

RESULTS

Out of 288 health subcentres, GIS identified 10 hot spots at extremely high risk of malaria and 14 hot spots at high risk of malaria. Malaria may flare up in these hot spots whenever favourable transmission conditions arise. Health authorities have been advised to establish control measures in these selected hot spots for timely prevention.

CONCLUSION

There is a need for adequate monitoring and allocation of available resources for better interventions in the malaria hotspots. The GIS model used in this study can be used, even at village or cluster level, to pin point the malaria hot spots, and information can be updated and retrieved easily.

The distribution and bionomics of anopheles malaria vector mosquitoes in Indonesia

Malaria remains one of the greatest human health burdens in Indonesia. Although Indonesia has a long and renowned history in the early research and discoveries of malaria and subsequently in the successful use of environmental control methods to combat the vector, much remains unknown about many of these mosquito species. There are also significant gaps in the existing knowledge on the transmission epidemiology of malaria, most notably in the highly malarious eastern half of the archipelago. These compound the difficulty of developing targeted and effective control measures. The sheer complexity and number of malaria vectors in the country are daunting. The difficult task of summarizing the available information for each species and/or species complex is compounded by the patchiness of the data: while relatively plentiful in one area or region, it can also be completely lacking in others. Compared to many other countries in the Oriental and Australasian biogeographical regions, only scant information on vector bionomics and response to chemical measures is available in Indonesia. That information is often either decades old, geographically patchy or completely lacking. Additionally, a large number of information sources are published in Dutch or Indonesian language and therefore less accessible. This review aims to present an updated overview of the known distribution and bionomics of the 20 confirmed malaria vector species or species complexes regarded as either primary or secondary (incidental) malaria vectors within Indonesia. This chapter is not an exhaustive review of each of these species. No attempt is made to specifically discuss or resolve the taxonomic record of listed species in this document, while recognizing the ever evolving revisions in the systematics of species groups and complexes. A review of past and current status of insecticide susceptibility of eight vector species of malaria is also provided.

Tackling the malaria problem in the South-East Asia Region: need for a change in policy?

Malaria is largely neglected in the South-East Asia Region (SEAR), although it has the highest number of people susceptible to the disease. Malaria in the SEAR exhibits special epidemiological characteristics such as "forest malaria" and malaria due to migration across international borders. The Greater Mekong Subregion (GMS) has been a focal-point for the emergence of drug resistant malaria. With the recent emergence of artemisinin resistance, coupled with the limited availability of insecticides, malaria control efforts in the SEAR face a steep challenge. Indirect man-made factors such as climate change, as well as direct man-made factors such as the circulation of counterfeit drugs have added to the problem. Increased monitoring, surveillance, pharmacovigilance as well as cross-border collaboration are required to address these problems. Regional networking and data-sharing will keep all stakeholders updated about the status of various malaria control programmes in the SEAR. Cutting-edge technologies such as GIS/GPS (geographical information system/global positioning system) systems and mobile phones can provide information in "real-time". A holistic and sustained approach to malaria control by integrated vector management (IVM) is suggested, in which all the stakeholder countries work collaboratively as a consortium. This approach will address the malaria problem in a collective manner so that malaria control can be sustained over time.

Analysis of polymorphisms in the merozoite surface protein-3α gene and two microsatellite loci in Sri Lankan Plasmodium vivax: evidence of population substructure in Sri Lanka

The geographical distribution of genetic variation in Plasmodium vivax samples (N = 386) from nine districts across Sri Lanka is described using three markers; the P. vivax merozoite surface protein-3α (Pvmsp-3α) gene, and the two microsatellites m1501 and m3502. At Pvmsp-3α, 11 alleles were found with an expected heterozygosity (H(e)) of 0.81, whereas at m1501 and m3502, 24 alleles (H(e) = 0.85) and 8 alleles (H(e) = 0.74) were detected, respectively. Overall, 95 unique three locus genotypes were detected among the 279 samples positive at all three loci (H(e) = 0.95). Calculating the pairwise fixation index (F(ST)) revealed statistically significant population structure. The presence of identical 2-loci microsatellite genotypes in a significant proportion of samples revealed local clusters of closely related isolates contributing to strong linkage disequilibrium between marker alleles. The results show evidence of high genetic diversity and possible population substructure of P. vivax populations in Sri Lanka.

Theoretical investigation of malaria prevalence in two Indian cities using the response surface method

Background

Elucidation of the relationships between malaria incidence and climatic and non-climatic factors in a region is of utmost importance in understanding the causative factors of disease spread and design of control strategies. Very often malaria prevalence data is restricted to short time scales (months to few years). This demands application of rigorous statistical modelling techniques for analysis and prediction. The monthly malaria prevalence data for three to five years from two cities in southern India, situated in two different climatic zones, are studied to capture their dependence on climatic factors.

Methods

The statistical technique of response surface method (RSM) is applied for the first time to study any epidemiological data. A new step-by-step model reduction technique is proposed to refine the initial model obtained from RSM. This provides a simpler structure and gives better fit. This combined approach is applied to two types of epidemiological data (Slide Positivity Rates values and Total Malaria cases), for two cities in India with varying strengths of disease prevalence and environmental conditions.

Results

The study on these data sets reveals that RSM can be used successfully to elucidate the important environmental factors influencing the transmission of the disease by analysing short epidemiological time series. The proposed approach has high predictive ability over relatively long time horizons.

Conclusions

This method promises to provide reliable forecast of malaria incidence across varying environmental conditions, which may help in designing useful control programmes for malaria.

Malaria is an important differential diagnosis in visitors returning from Sri Lankan National Safari Parks

Diagnostic confusion may occur between dengue and malaria when febrile patients with thrombocytopenia return from travel to previous malaria endemic areas. Laboratory tests should include blood smear examination for malaria parasites even though current malaria endemicity in Sri Lanka is low.

Pre-elimination stage of malaria in Sri Lanka: assessing the level of hidden parasites in the population

BACKGROUND

With the dramatic drop in the transmission of malaria in Sri Lanka in recent years, the country entered the malaria pre-elimination stage in 2008. Assessing the community prevalence of hidden malaria parasites following several years of extremely low transmission is central to the process of complete elimination. The existence of a parasite reservoir in a population free from clinical manifestations, would influence the strategy for surveillance and control towards complete elimination.

METHODS

The prevalence of hidden parasite reservoirs in two historically malaria endemic districts, Anuradhapura and Kurunegala, previously considered as high malaria transmission areas in Sri Lanka, where peaks of transmission follow the rainy seasons was assessed. Blood samples of non-febrile individuals aged five to 55 years were collected from randomly selected areas in the two districts at community level and a questionnaire was used to collect demographic information and movement of the participants. A simple, highly sensitive nested PCR was carried out to detect both Plasmodium falciparum and Plasmodium vivax, simultaneously.

RESULTS

In total, 3,023 individuals from 101 villages participated from both districts comprising mostly adults between the ages 19-55 years. Out of these, only about 1.4% of them (n = 19) could recall having had malaria during the past five years. Analysis of a subset of samples (n = 1322) from the two districts using PCR showed that none of the participants had hidden parasites.

DISCUSSION

A reservoir of hidden parasites is unlikely to be a major concern or a barrier to the ongoing malaria elimination efforts in Sri Lanka. However, as very low numbers of indigenous cases are still recorded, an island-wide assessment and in particular, continued alertness and follow up action are still needed. The findings of this study indicate that any future assessments should be based on an adaptive sampling approach, involving prompt sampling of all subjects within a specified radius, whenever a malaria case is identified in a given focus.

High sensitivity detection of Plasmodium species reveals positive correlations between infections of different species, shifts in age distribution and reduced local variation in Papua New Guinea

Background

When diagnosed by standard light microscopy (LM), malaria prevalence can vary significantly between sites, even at local scale, and mixed species infections are consistently less common than expect in areas co-endemic for Plasmodium falciparum, Plasmodium vivax and Plasmodium malariae. The development of a high-throughput molecular species diagnostic assay now enables routine PCR-based surveillance of malaria infections in large field and intervention studies, and improves resolution of species distribution within and between communities.

Methods

This study reports differences in the prevalence of infections with all four human malarial species and of mixed infections as diagnosed by LM and post-PCR ligase detection reaction – fluorescent microsphere (LDR-FMA) assay in 15 villages in the central Sepik area of Papua New Guinea.

Results

Significantly higher rates of infection by P. falciparum, P. vivax, P. malariae and Plasmodium ovale were observed in LDR-FMA compared to LM diagnosis (p < 0.001). Increases were particularly pronounced for P. malariae (3.9% vs 13.4%) and P. ovale (0.0% vs 4.8%). In contrast to LM diagnosis, which suggested a significant deficit of mixed species infections, a significant excess of mixed infections over expectation was detected by LDR-FMA (p < 0.001). Age of peak prevalence shifted to older age groups in LDR-FMA diagnosed infections for P. falciparum (LM: 7–9 yrs 47.5%, LDR-FMA: 10–19 yrs 74.2%) and P. vivax (LM: 4–6 yrs 24.2%, LDR-FMA: 7–9 yrs 50.9%) but not P. malariae infections (10–19 yrs, LM: 7.7% LDR-FMA: 21.6%). Significant geographical variation in prevalence was found for all species (except for LM-diagnosed P. falciparum), with the extent of this variation greater in LDR-FMA than LM diagnosed infections (overall, 84.4% vs. 37.6%). Insecticide-treated bednet (ITN) coverage was also the dominant factor linked to geographical differences in Plasmodium species infection prevalence explaining between 60.6% – 74.5% of this variation for LDR-FMA and 81.8% – 90.0% for LM (except P. falciparum), respectively.

Conclusion

The present study demonstrates that application of molecular diagnosis reveals patterns of malaria risk that are significantly different from those obtained by standard LM. Results provide insight relevant to design of malaria control and eradication strategies.

Models for short term malaria prediction in Sri Lanka

Background

Malaria in Sri Lanka is unstable and fluctuates in intensity both spatially and temporally. Although the case counts are dwindling at present, given the past history of resurgence of outbreaks despite effective control measures, the control programmes have to stay prepared. The availability of long time series of monitored/diagnosed malaria cases allows for the study of forecasting models, with an aim to developing a forecasting system which could assist in the efficient allocation of resources for malaria control.

Methods

Exponentially weighted moving average models, autoregressive integrated moving average (ARIMA) models with seasonal components, and seasonal multiplicative autoregressive integrated moving average (SARIMA) models were compared on monthly time series of district malaria cases for their ability to predict the number of malaria cases one to four months ahead. The addition of covariates such as the number of malaria cases in neighbouring districts or rainfall were assessed for their ability to improve prediction of selected (seasonal) ARIMA models.

Results

The best model for forecasting and the forecasting error varied strongly among the districts. The addition of rainfall as a covariate improved prediction of selected (seasonal) ARIMA models modestly in some districts but worsened prediction in other districts. Improvement by adding rainfall was more frequent at larger forecasting horizons.

Conclusion

Heterogeneity of patterns of malaria in Sri Lanka requires regionally specific prediction models. Prediction error was large at a minimum of 22% (for one of the districts) for one month ahead predictions. The modest improvement made in short term prediction by adding rainfall as a covariate to these prediction models may not be sufficient to merit investing in a forecasting system for which rainfall data are routinely processed.

Temporal correlation between malaria and rainfall in Sri Lanka

Background

Rainfall data have potential use for malaria prediction. However, the relationship between rainfall and the number of malaria cases is indirect and complex.

Methods

The statistical relationships between monthly malaria case count data series and monthly mean rainfall series (extracted from interpolated station data) over the period 1972 – 2005 in districts in Sri Lanka was explored in four analyses: cross-correlation; cross-correlation with pre-whitening; inter-annual; and seasonal inter-annual regression.

Results

For most districts, strong positive correlations were found for malaria time series lagging zero to three months behind rainfall, and negative correlations were found for malaria time series lagging four to nine months behind rainfall. However, analysis with pre-whitening showed that most of these correlations were spurious. Only for a few districts, weak positive (at lags zero and one) or weak negative (at lags two to six) correlations were found in pre-whitened series. Inter-annual analysis showed strong negative correlations between malaria and rainfall for a group of districts in the centre-west of the country. Seasonal inter-annual analysis showed that the effect of rainfall on malaria varied according to the season and geography.

Conclusion

Seasonally varying effects of rainfall on malaria case counts may explain weak overall cross-correlations found in pre-whitened series, and should be taken into account in malaria predictive models making use of rainfall as a covariate.

Cutaneous leishmaniasis in southern Sri Lanka

Cutaneous leishmaniasis is an established disease in Sri Lanka. The majority of cases have been reported from the North-Central Province, with the southern parts of the country considered less affected. However, during 2004, when the services of a dermatologist were available, a considerable number of patients were referred from the Southern Province, which formed the basis for this study. The clinical pattern, detailed geographical distribution within the Southern Province and periodicity of the cases were studied over a period of 12 months. Of the 113 patients diagnosed, the highest number was within the 10-19 years age group. Most patients were from densely populated rural areas around Matara, a large town within this province. There was a notable increase in the number of cases presenting during February-March and August-September, which are periods following monsoonal rains. Exposed areas of the skin were commonly affected, with the majority of patients having single lesions. Females and males were equally affected. This is in contrast to our previous findings in the North-Central Province where the majority of patients were male soldiers with multiple lesions.

Island-wide diversity in single nucleotide polymorphisms of the Plasmodium vivax dihydrofolate reductase and dihydropteroate synthetase genes in Sri Lanka

BACKGROUND

Single nucleotide polymorphisms (SNPs) in the Plasmodium vivax dihydrofolate reductase (Pfdhfr) and dihydropteroate synthetase (Pvdhps) genes cause parasite resistance to the antifolate drug combination, sulphadoxine/pyrimethamine (SP). Monitoring these SNPs provide insights into the level of drug pressure caused by SP use and presumably other antifolate drugs. In Sri Lanka, chloroquine (CQ) with primaquine (PQ) and SP with PQ is used as first and second line treatment, respectively, against uncomplicated Plasmodium falciparum and/or P. vivax infections. CQ/PQ is still efficacious against P. vivax infections, thus SP is rarely used and it is assumed that the prevalence of SNPs related to P. vivax SP resistance is low. However, this has not been assessed in Sri Lanka as in most other parts of Asia. This study describes the prevalence and distribution of SNPs related to P. vivax SP resistance across Sri Lanka.

SUBJECTS AND METHODS

P. vivax-positive samples were collected from subjects presenting at government health facilities across nine of the major malaria endemic districts on the island. The samples were analysed for SNPs/haplotypes at codon 57, 58, 61 and 117 of the Pvdhfr gene and 383, 553 and 585 of the Pvdhps gene by applying PCR followed by a hybridization step using sequence specific oligonucleotide probes (SSOPs) in an ELISA format.

RESULTS

In the study period, the government of Sri Lanka recorded 2,149 P. vivax cases from the nine districts out of which, 454 (21.1%) blood samples were obtained. Pvdhfr haplotypes could be constructed for 373 of these. The FSTS wild-haplotype was represented in 257 samples (68.9%), the double mutant LRTS haplotype was the most frequently observed mutant (24.4%) while the triple mutation (LRTN) was only identified once. Except for two samples of the single mutated Pvdhps GAV haplotype, the remaining samples were wildtype. Geographical differences were apparent, notably a significantly higher frequency of mutant Pvdhfr haplotypes was observed in the Northern districts.

CONCLUSION

Since SP is rarely used in Sri Lanka, the high frequency and diversity of Pvdhfr mutations was unexpected indicating the emergence of drug resistant parasites despite a low level of SP drug pressure.

Assembling a global database of malaria parasite prevalence for the Malaria Atlas Project

BACKGROUND

Open access to databases of information generated by the research community can synergize individual efforts and are epitomized by the genome mapping projects. Open source models for outputs of scientific research funded by tax-payers and charities are becoming the norm. This has yet to be extended to malaria epidemiology and control.

METHODS

The exhaustive searches and assembly process for a global database of malaria parasite prevalence as part of the Malaria Atlas Project (MAP) are described. The different data sources visited and how productive these were in terms of availability of parasite rate (PR) data are presented, followed by a description of the methods used to assemble a relational database and an associated geographic information system. The challenges facing spatial data assembly from varied sources are described in an effort to help inform similar future applications.

RESULTS

At the time of writing, the MAP database held 3,351 spatially independent PR estimates from community surveys conducted since 1985. These include 3,036 Plasmodium falciparum and 1,347 Plasmodium vivax estimates in 74 countries derived from 671 primary sources. More than half of these data represent malaria prevalence after the year 2000.

CONCLUSION

This database will help refine maps of the global spatial limits of malaria and be the foundation for the development of global malaria endemicity models as part of MAP. A widespread application of these maps is envisaged. The data compiled and the products generated by MAP are planned to be released in June 2009 to facilitate a more informed approach to global malaria control.

Space-time clustering of childhood malaria at the household level: a dynamic cohort in a Mali village

BACKGROUND

Spatial and temporal heterogeneities in the risk of malaria have led the WHO to recommend fine-scale stratification of the epidemiological situation, making it possible to set up actions and clinical or basic researches targeting high-risk zones. Before initiating such studies it is necessary to define local patterns of malaria transmission and infection (in time and in space) in order to facilitate selection of the appropriate study population and the intervention allocation. The aim of this study was to identify, spatially and temporally, high-risk zones of malaria, at the household level (resolution of 1 to 3 m).

METHODS

This study took place in a Malian village with hyperendemic seasonal transmission as part of Mali-Tulane Tropical Medicine Research Center (NIAID/NIH). The study design was a dynamic cohort (22 surveys, from June 1996 to June 2001) on about 1300 children (<12 years) distributed between 173 households localized by GPS. We used the computed parasitological data to analyzed levels of Plasmodium falciparum, P. malariae and P. ovale infection and P. falciparum gametocyte carriage by means of time series and Kulldorff's scan statistic for space-time cluster detection.

RESULTS

The time series analysis determined that malaria parasitemia (primarily P. falciparum) was persistently present throughout the population with the expected seasonal variability pattern and a downward temporal trend. We identified six high-risk clusters of P. falciparum infection, some of which persisted despite an overall tendency towards a decrease in risk. The first high-risk cluster of P. falciparum infection (rate ratio = 14.161) was detected from September 1996 to October 1996, in the north of the village.

CONCLUSION

This study showed that, although infection proportions tended to decrease, high-risk zones persisted in the village particularly near temporal backwaters. Analysis of this heterogeneity at the household scale by GIS methods lead to target preventive actions more accurately on the high-risk zones identified. This mapping of malaria risk makes it possible to orient control programs, treating the high-risk zones identified as a matter of priority, and to improve the planning of intervention trials or research studies on malaria.

Comparison of naturally acquired antibody responses against the C-terminal processing products of Plasmodium vivax Merozoite Surface Protein-1 under low transmission and unstable malaria conditions in Sri Lanka

We report here, for the first time, a comparison of naturally acquired antibody responses to the 42 and 19 kDa C-terminal processing products of Plasmodium vivax Merozoite Surface Protein-1 assayed by ELISA using p42 and p19 baculovirus-derived recombinant proteins, respectively. Test populations comprised patients with microscopy confirmed acute P. vivax infections from two regions endemic for vivax malaria where low transmission and unstable malaria conditions prevail, and a non-endemic urban area, in Sri Lanka. The antibody prevalence to the two proteins, both at the individual and population levels, tend to respond more to p42 than to p19 in all test areas, where >14% of individuals preferentially recognized p42, compared with <2% for p19. In patients with no previous exposure to malaria, 21% preferentially recognized p42, whereas none exclusively recognized p19. A significantly lower prevalence of anti-p19 IgM, but not anti-p42 IgM, was observed among residents from endemic areas compared with their non-endemic counterparts. Individuals from both endemic areas produced significantly less anti-p19 IgM compared with anti-p42 IgM. IgG1 was the predominant IgG isotype for both antigens in all individuals. With increasing exposure to malaria in both endemic areas, anti-p19 antibody responses were dominated by the functionally important IgG1 and IgG3 isotypes, with a concurrent reduction in IgM that was lacking in the non-endemic residents. This antibody switch was also reflected for PvAMA-1 as we previously reported with the identical battery of sera. In contrast, the antibody switch for p42 was restricted to endemic residents with more extensive exposure. These results suggest that an IgM-dominated antibody response against the p42 polymorphic region in endemic residents may interfere with the development of an IgG-dominated "protective" isotype shift to p19, that may complicate vaccine development.

Malaria in Sri Lanka: one year post-tsunami

One year ago, the authors of this article reported in this journal on the malaria situation in Sri Lanka prior to the tsunami that hit on 26 December 2004, and estimated the likelihood of a post-tsunami malaria outbreak to be low. Malaria incidence has decreased in 2005 as compared to 2004 in most districts, including the ones that were hit hardest by the tsunami. The malaria incidence (aggregated for the whole country) in 2005 followed the downward trend that started in 2000. However, surveillance was somewhat affected by the tsunami in some coastal areas and the actual incidence in these areas may have been higher than recorded, although there were no indications of this and it is unlikely to have affected the overall trend significantly. The focus of national and international post tsunami malaria control efforts was supply of antimalarials, distribution of impregnated mosquito nets and increased monitoring in the affected area. Internationally donated antimalarials were either redundant or did not comply with national drug policy, however, few seem to have entered circulation outside government control. Despite distribution of mosquito nets, still a large population is relatively exposed to mosquito bites due to inadequate housing. There were no indications of increased malaria vector abundance. Overall it is concluded that the tsunami has not negatively influenced the malaria situation in Sri Lanka.

The Sri Lanka Tsunami Experience

The Indian Ocean tsunami of 2004 killed 31,000 people in Sri Lanka and produced morbidity primarily resulting from near-drownings and traumatic injuries. In the immediate aftermath, the survivors brought bodies to the hospitals, which hampered the hospitals' operations. The fear of epidemics led to mass burials. Infectious diseases were prevented through the provision of clean water and through vector control. Months after the tsunami, little rebuilding of permanent housing was evident, and many tsunami victims continued to reside in transit camps without means of generating their own income. The lack of an incident command system, limited funding, and political conflicts were identified as barriers to optimal relief efforts. Despite these barriers, Sri Lanka was fortunate in drawing upon a well-developed community health infrastructure as well as local and international resources. The need continues for education and training in clinical skills for mass rescue and emergency treatment, as well as participation in a multidisciplinary response.

Natural human antibody responses to Plasmodium vivax apical membrane antigen 1 under low transmission and unstable malaria conditions in Sri Lanka

Plasmodium vivax apical membrane antigen 1, an important malaria vaccine candidate, was immunogenic during natural malaria infections in Sri Lanka, where low transmission and unstable malaria conditions prevail. Antibody prevalence increased with exposure in areas where malaria was or was not endemic. A marked isotype switch to cytophilic (immunoglobulin G1 [IgG1]/IgG3) antibodies was evident with increasing exposure exclusively in residents from areas of endemicity.

Spatiotemporal distribution of insecticide resistance in Anopheles culicifacies and Anopheles subpictus in Sri Lanka

The malaria situation in Sri Lanka worsened during the 1990s with the emergence and spread of resistance to the drugs and insecticides used for control. Chloroquine resistance has increased rapidly over this period, but adverse changes in malaria transmission are more closely associated with insecticide use rather than drug resistance. Insecticide susceptibility tests were routinely carried out in key anopheline vectors across the country for more than a decade. These sentinel data were combined with data collected by other research programmes and used to map the spatial and temporal trends of insecticide resistance in the main vectors, Anopheles culicifacies and A. subpictus, and to examine the relationship between insecticide resistance, changes in national spraying regimens and malaria prevalence. Both species had widespread resistance to malathion, the insecticide of choice in the early 1990s. Both species were initially susceptible to the organophosphate and pyrethroid insecticides used operationally from 1993, but some resistance has now been selected. The levels of malathion and fenitrothion resistance in A. subpictus were higher in some ecological regions than others, which may be related to the distribution of sibling species, agricultural pesticide exposure and/or environmental factors. The study highlights that the emergence and spread of insecticide resistance is a constant threat and that active surveillance systems are vital in identifying key vectors and evidence of resistance.

Maps of the Sri Lanka malaria situation preceding the tsunami and key aspects to be considered in the emergency phase and beyond

Background

Following the tsunami, a detailed overview of the area specific transmission levels is essential in assessing the risk of malaria in Sri Lanka. Recent information on vector insecticide resistance, parasite drug resistance, and insights into the national policy for malaria diagnosis and treatment are important in assisting national and international agencies in their control efforts.

Methods

Monthly records over the period January 1995 – October 2004 of confirmed malaria cases were used to perform an analysis of malaria distribution at district spatial resolution. Also, a focused review of published reports and routinely collected information was performed.

Results

The incidence of malaria was only 1 case per thousand population in the 10 months leading up to the disaster, in the districts with the highest transmission.

Conclusion

Although relocated people may be more exposed to mosquito bites, and their capacity to handle diseases affected, the environmental changes caused by the tsunami are unlikely to enhance breeding of the principal vector, and, given the present low parasite reservoir, the likelihood of a malaria outbreak is low. However, close monitoring of the situation is necessary, especially as December – February is normally the peak transmission season. Despite some losses, the Sri Lanka public health system is capable of dealing with the possible threat of a malaria outbreak after the tsunami. The influx of foreign medical assistance, drugs, and insecticides may interfere with malaria surveillance, and the long term malaria control strategy of Sri Lanka, if not in accordance with government policy.

The relationship between the Plasmodium falciparum parasite ratio in childhood and climate estimates of malaria transmission in Kenya

Background

Plasmodium falciparum morbid and fatal risks are considerably higher in areas supporting parasite prevalence ≥25%, when compared with low transmission areas supporting parasite prevalence below 25%. Recent descriptions of the health impacts of malaria in Africa are based upon categorical descriptions of a climate-driven fuzzy model of suitability (FCS) for stable transmission developed by the Mapping Malaria Risk in Africa collaboration (MARA).

Methods

An electronic and national search was undertaken to identify community-based parasite prevalence surveys in Kenya. Data from these surveys were matched using ArcView 3.2 to extract spatially congruent estimates of the FCS values generated by the MARA model. Levels of agreement between three classes used during recent continental burden estimations of parasite prevalence (0%, >0 – <25% and ≥25%) and three classes of FCS (0, >0 – <0.75 and ≥0.75) were tested using the kappa (k) statistic and examined as continuous variables to define better levels of agreement.

Results

Two hundred and seventeen independent parasite prevalence surveys undertaken since 1980 were identified during the search. Overall agreement between the three classes of parasite prevalence and FCS was weak although significant (k = 0.367, p < 0.0001). The overall correlation between the FCS and the parasite ratio when considered as continuous variables was also positive (0.364, p < 0.001). The margins of error were in the stable, endemic (parasite ratio ≥25%) class with 42% of surveys represented by an FCS <0.75. Reducing the FCS value criterion to ≥0.6 improved the classification of stable, endemic parasite ratio surveys. Zero values of FCS were not adequate discriminators of zero parasite prevalence.

Conclusion

Using the MARA model to categorically distinguish populations at differing intensities of malaria transmission in Kenya may under-represent those who are exposed to stable, endemic transmission and over-represent those at no risk. The MARA approach to defining FCS values of suitability for stable transmission represents our only contemporary continental level map of malaria in Africa but there is a need to redefine Africa's population at risk in accordance with both climatic and non-climatic determinants of P. falciparum transmission intensity to provide a more informed approach to estimating the morbid and fatal consequences of infection across the continent.

A malaria risk analysis in an irrigated area in Sri Lanka

Malaria in Sri Lanka is unstable and epidemic, with large spatial and temporal differences in transmission dynamics. The disease is of great public health significance and identification of underlying risk factors is important in order to use the limited resources in a cost-effective way. The International Water Management Institute (IWMI) recently launched a project of GIS-based malaria risk mapping in Sri Lanka, to investigate whether this tool could be used for epidemic forecasting and for the planning of malaria control activities. This paper presents results for the Uda Walawe region in southern Sri Lanka, an irrigated agricultural area where malaria cases were mapped at the smallest administrative level for each month over a 10-year period. Malaria incidence rates were related to land- and water-use patterns, socio-economic features, and data on malaria control interventions in a multivariate analysis. Areas of high malaria risk were characterized by: (i) higher than average rainfall, (ii) greater forest coverage; (iii) slash and burn cultivation as a predominant agricultural activity; (iv) presence of many abandoned irrigation reservoirs; and (v) poor socio-economic status. Irrigated rice cultivation areas had a lower risk of malaria than non-irrigated areas. This difference could be due to socio-economic factors related to irrigation development and/or transmission dynamics related to vector density or species composition. Our findings call for malaria control strategies that are readily adapted to different ecological and epidemiological settings. Malaria risk maps are a convenient tool for discussing targeted and cost-effective interventions with disease control personnel.