Epidemic malaria in India and the El Niño southern oscillation

Changes in the associations between malaria incidence and climatic factors across malaria endemic countries in Africa and Asia-Pacific region

Empirical evidence supporting the associations between malaria incidence and climatic factors has remained controversial, buffering the progress in the Global Malaria Program that aims to eliminate 90% of the world malaria burden by 2030. This study has aimed to evaluate the nature and extent at which these relations are maintained across all the malaria endemic countries of Africa and Asia-Pacific region. We have utilized the last two decades of malaria incidence, annual minimum temperature, and annual precipitation time series data (2000-2020) for the two most malaria-impacted regions. These data were fitted in the generalized linear model and the mixed effects model. The results showed that there exists a large heterogeneity in malaria incidence across the countries, and between the regions. Last two decadal tendencies showed significant reductions in the disease burden in almost all the countries in the Asia Pacific, with several exceptions or relatively slowed reductions in the Africa. We found significant changes in the positive linear associations between malaria incidence, annual minimum temperature, and annual precipitation across African countries. Many Asia-Pacific countries namely Bangladesh, Bhutan, Indonesia, South Korea, Nepal, Thailand, Vietnam showed negative effects in the associations with the annual precipitation. This study indicates that increasing temperature within the range of 12-30 °C can generate positive effects on malaria incidence, but the nature and extent of precipitation effects vary across countries and at a large regional scale.

Description of malaria epidemics and normal transmissions using rainfall variability in Gondar Zuria highland District, Ethiopia

Background

Rainfall is one of the climate variables most studied as it affects malaria occurrence directly.

Objective

This study aimed to describe how monthly rainfall variability affects malaria incidence in different years.

Methods

A total of 7 years (2013/14-2019/20) retrospective confirmed and treated malaria cases in Gondar Zuria district were used for analysis in addition to five (2013/14-2017/18) years retrospective data from Dembia district.

Results

The annual rainfalls in the study years showed no statistically significant difference (p = 0. 78). But, variations in rainfalls of the different months (p = 0.000) of the different years were the source of variations for malaria count (incidences) in the different years. Malaria was transmitted throughout the year with the highest peak in November (mean count = 1468.7 ± 697.8) and followed by May (mean count = 1253.4 ± 1391.8), after main Kiremt/Summer and minor Bulg/Spring rains respectively. The lowest transmission was occurred in February (338 ± 240.3) when the rivers were the only source of mosquito vectors. Year 2013/14 (RF = 2351.12 mm) and 2019/20 (RF = 2278.80 mm) with no statistically significant difference (p = 0.977) in annual rainfalls produced 10, 702 (49.2%) and 961 (20%) malaria counts for the Bulg (spring) season respectively due to 581.92 mm (24.8%) higher total Bulg/Spring rain in 2013/14 compared to 124.1 mm (5.45%) in 2019/20. Generally, above normal rainfalls in Bulg/Spring season increased malaria transmission by providing more aquatic habitats supporting the growth of the immature stages. But heavy rains in Summer/Kiremt produced low malaria counts due to the high intensity of the rainfalls which could kill the larvae and pupae. Spearman's correlation analysis indicated that the mean rainfalls of current month (RF) (0 lagged month) (P = 0.025), previous month (RF1) (1 month lagged) (p = 0.000), before previous months (RF2) (2 months lagged) (p = 0.001) and mean RF + RF1 + RF2 (P = 0.001) were positive significantly correlated with mean monthly malaria counts compared to negative significant correlations for temperature variables. Temperature variables negative correlations were interpreted as confounding effects because decreased malaria counts in dry months were due to a decrease in rainfalls. Conclusion: rainfall distribution in different months of a year affects malaria occurrences.

A systematic evidence review of the effect of climate change on malaria in Iran

Climate is an effective factor in the ecological structure which plays an important role in control and outbreak of the diseases caused by biological factors like malaria. With regard to the occurring climatic change, this study aimed to review the effects of climate change on malaria in Iran. In this systematic review, Cochrane, PubMed and ScienceDirect (as international databases), SID and Magiran as Persian databases were investigated through MESH keywords including climate change, global warming, malaria, Anopheles, and Iran. The related articles were screened and finally their results were extracted using data extraction sheets. Totally 41 papers were resulted through databases searching process. Finally 14 papers which met inclusion criteria were included in data extraction stage. The findings indicated that Anopheles mosquitoes are present at least in 115 places in Iran; they are compatible with climatic zones of Iran. Malaria and it's vectors are affected by climate change. Temperature, precipitation, relative humidity, wind intensity and direction are the most important climatic factors affecting the growth and proliferation of Anopheles, Plasmodium and the prevalence of malaria. The transmission of malaria in Iran is associated with the climatic factors of temperature, rainfall, and humidity. Therefore, with regard to the occurring climatic change, the incidence of the disease may also change which needs to be taken into consideration while planning of malaria control.

Exploring the Impact of Climate Variability on Malaria Transmission Using a Dynamic Mosquito-Human Malaria Model

Introduction:

The reasons for malaria resurgence mostly in Africa are yet to be well understood. Although the causes are often linked to regional climate change, it is important to understand the impact of climate variability on the dynamics of the disease. However, this is almost impossible without adequate long-term malaria data over the study areas.

Methods:

In this study, we develop a climate-based mosquito-human malaria model to study malaria dynamics in the human population over KwaZulu-Natal, one of the epidemic provinces in South Africa, from 1970-2005. We compare the model output with available observed monthly malaria cases over the province from September 1999 to December 2003. We further use the model outputs to explore the relationship between the climate variables (rainfall and temperature) and malaria incidence over the province using principal component analysis, wavelet power spectrum and wavelet coherence analysis. The model produces a reasonable fit with the observed data and in particular, it captures all the spikes in malaria prevalence.

Results:

Our results highlight the importance of climate factors on malaria transmission and show the seasonality of malaria epidemics over the province. Results from the principal component analyses further suggest that, there are two principal factors associated with climates variables and the model outputs. One of the factors indicate high loadings on Susceptible, Exposed and Infected human, while the other is more correlated with Susceptible and Recovered humans. However, both factors reveal the inverse correlation between Susceptible-Infected and Susceptible-Recovered humans respectively. Through the spectrum analysis, we notice a strong annual cycle of malaria incidence over the province and ascertain a dominant of one year periodicity. Consequently, our findings indicate that an average of 0 to 120-day lag is generally noted over the study period, but the 120-day lag is more associated with temperature than rainfall. This is consistence with other results obtained from our analyses that malaria transmission is more tightly coupled with temperature than with rainfall in KwaZulu-Natal province.

El Niño Southern Oscillation as an early warning tool for malaria outbreaks in India

BACKGROUND

Risks of malaria epidemics in relation to El Niño and Southern Oscillation (ENSO) events have been mapped and studied at global level. In India, where malaria is a major public health problem, no such effort has been undertaken that inter-relates El Niño, Indian Summer Monsoon Rainfall (ISMR) and malaria. The present study has been undertaken to find out the relationship between ENSO events, ISMR and intra-annual variability in malaria cases in India, which in turn could help mitigate the malaria outbreaks.

METHODS

Correlation coefficients among 'rainfall index' (ISMR), '+ winter ONI' (NDJF) and 'malaria case index' were calculated using annual state-level data for the last 22 years. The 'malaria case index' representing 'relative change from mean' was correlated to the 4 month (November-February) average positive Oceanic Niño Index (ONI). The resultant correlations between '+ winter ONI' and 'malaria case index' were further analysed on geographical information system platform to generate spatial correlation map.

RESULTS

The correlation between '+ winter ONI' and 'rainfall index' shows that there is great disparity in effect of ENSO over ISMR distribution across the country. Correlation between 'rainfall index' and 'malaria case index' shows that malaria transmission in all geographical regions of India are not equally affected by the ISMR deficit or excess. Correlation between '+ winter ONI' and 'malaria case index' was found ranging from -0.5 to + 0.7 (p < 0.05). A positive correlation indicates that increase in El Niño intensity (+ winter ONI) will lead to rise in total malaria cases in the concurrent year in the states of Orissa, Chhattisgarh, Jharkhand, Bihar, Goa, eastern parts of Madhya Pradesh, part of Andhra Pradesh, Uttarakhand and Meghalaya. Whereas, negative correlations were found in the states of Rajasthan, Haryana, Gujarat, part of Tamil Nadu, Manipur, Mizoram and Sikkim indicating the likelihood of outbreaks in La Nina condition.

CONCLUSIONS

The generated map, representing spatial correlation between ' + winter ONI' and 'malaria case index', indicates positive correlations in eastern part, while negative correlations in western part of India. This study provides plausible guidelines to national programme for planning intervention measures in view of ENSO events. For better resolution, district level study with inclusion of IOD and 'epochal variation of monsoon rainfall' factors at micro-level is desired for better forecast of malaria outbreaks in the regions with 'no correlation'.

Dinámica de la epidemia de malaria en Colombia: Predicción probabilística temporal

Objetivo Realizar una predicción de la dinámica de la epidemia de malaria para el 2007 en Colombia con base en el análisis de la dinámica geométrica de 1960-2006 como una caminata al azar probabilista.Materiales y Métodos Basados en la caminata al azar probabilística se estudió la dinámica geométrica del número de casos anuales de malaria registrados en Colombia durante los años 1960-2006, analizando el comportamiento probabilístico de aumentos y disminuciones consecutivos, y el comportamiento probabilístico de casos durante rangos de años consecutivos, para así realizar una predicción temporal de los casos.Resultados Se desarrolló una metodología sencilla y acausal  que predice los valores extremos 81 003 y 104 098 para el número de infectados en el año 2007, predicción que fue refinada con el análisis de las variaciones anuales obteniendo un valor de 104 098 para el número de infectados en el año 2007. Esta predicción fue posteriormente corroborada con los datos del Instituto Nacional de Salud de Colombia, correspondiendo al 95,6 % respecto al número de casos reportados.Conclusión La comprensión del fenómeno acausal a partir de la caminata al azar probabilística permite realizar predicciones temporales, simples y prácticas, directamente comprobables y aplicables, economizando tiempo y recursos.

Malaria elimination in India and regional implications

The malaria situation in India is complex as a result of diverse socio-environmental conditions. India contributes a substantial burden of malaria outside sub-Saharan Africa, with the third highest Plasmodium vivax prevalence in the world. Successful malaria control in India is likely to enhance malaria elimination efforts in the region. Despite modest gains, there are many challenges for malaria elimination in India, including: varied patterns of malaria transmission in different parts of the country demanding area-specific control measures; intense malaria transmission fuelled by favourable climatic and environment factors; varying degrees of insecticide resistance of vectors; antimalarial drug resistance; a weak surveillance system; and poor national coordination of state programmes. Prevention and protection against malaria are low as a result of a weak health-care system, as well as financial and socioeconomic constraints. Additionally, the open borders of India provide a potential route of entry for artesunate-resistant parasites from southeast Asia. This situation calls for urgent dialogue around tackling malaria across borders-between India's states and neighbouring countries-through sharing of information and coordinated control and preventive measures, if we are to achieve the aim of malaria elimination in the region.

Macroecological patterns of American Cutaneous Leishmaniasis transmission across the health areas of Panamá (1980-2012)

American Cutaneous Leishmaniasis (ACL) is a neglected vector-borne zoonosis that persists despite increasing socio-economic development and urbanization in Panamá. Here, we investigate the association between environmental changes and spatio-temporal ACL transmission in the Republic of Panamá (1980-2012). We employ a macroecological approach, where patterns of variation in ACL incidence at the spatially coarse-grained scale of health areas are studied considering factors linked to the ecology of ACL transmission. We specifically study impacts of climatic variability, measured by the different phases of El Niño Southern Oscillation (ENSO), within diverse ecosystems and sand fly (Diptera: Psychodidae) vector species, as well as heterogeneous local climatic patterns, deforestation, population growth rates, and changes in social marginalization. We found that over the study period, patterns of ACL incidence: (i) were asynchronous with clusters changing from east to west of the Panamá Canal, (ii) trends increased in the west, and decreased or remained nearly constant in the east, independent of human population growth, (iii) generally increased in years following El Niño, and (iv) decreased as forest cover increased. We found no significant association between changes in socio-economic indicators and ACL transmission. Regarding vector abundance and presence, we found that studies had been biased to locations east of the Panamá canal, and that, in general, the abundance of dominant vector species decreased during the cold phase of ENSO. Finally, our results indicate that a macroecological approach is useful to understand heterogeneities related to environmental change impacts on ACL transmission.

The potential elimination of Plasmodium vivax malaria by relapse treatment: insights from a transmission model and surveillance data from NW India

Background

With over a hundred million annual infections and rising morbidity and mortality, Plasmodium vivax malaria remains largely a neglected disease. In particular, the dependence of this malaria species on relapses and the potential significance of the dormant stage as a therapeutic target, are poorly understood.

Methodology/Principal Findings

To quantify relapse parameters and assess the population-wide consequences of anti-relapse treatment, we formulated a transmission model for P. vivax suitable for parameter inference with a recently developed statistical method based on routine surveillance data. A low-endemic region in NW India, whose strong seasonality demarcates the transmission season, provides an opportunity to apply this modeling approach. Our model gives maximum likelihood estimates of 7.1 months for the mean latency and 31% for the relapse rate, in close agreement with regression estimates and clinical evaluation studies in the area. With a baseline of prevailing treatment practices, the model predicts that an effective anti-relapse treatment of 65% of those infected would result in elimination within a decade, and that periodic mass treatment would dramatically reduce the burden of the disease in a few years.

Conclusion/Significance

The striking dependence of P. vivax on relapses for survival reinforces the urgency to develop more effective anti-relapse treatments to replace Primaquine (PQ), the only available drug for the last fifty years. Our methods can provide alternative and simple means to estimate latency times and relapse frequency using routine epidemiological data, and to evaluate the population-wide impact of relapse treatment in areas similar to our study area.

Plasmodium vivax, one of the four species responsible for malaria in humans, represents today a much larger global public health problem than previously recognized. The neglect of P. vivax is still apparent in the limited efforts made so far to understand the regional dynamics of the disease, and in the non-existence of practical models to guide and evaluate control measures. One main impediment is the overall uncertainty in the dynamic role of the hidden reservoir, resulting from the liver stage known as hypnozoites and responsible for relapses, a characteristic feature of this species. Current control efforts and elimination plans are therefore hampered in their ability to quantify the impact of effective anti-relapse treatments. This paper applies a P. vivax transmission model to surveillance data from a semi-arid region (in NW India), whose clear demarcation of the transmission and relapse seasons makes it especially suited for estimating relapse parameters such as frequency and rate. The model results quantify the striking dependence of P. vivax on relapses for its survival, supporting the feasibility of regional elimination and lending support to the expressed urgency of replacing Primaquine, the anti- relapse drug now in use for over fifty years with unsatisfactory efficacy, resistance and side-effects.

Impacts of climate change on public health in India: future research directions

BACKGROUND

Climate change and associated increases in climate variability will likely further exacerbate global health disparities. More research is needed, particularly in developing countries, to accurately predict the anticipated impacts and inform effective interventions.

OBJECTIVES

Building on the information presented at the 2009 Joint Indo-U.S. Workshop on Climate Change and Health in Goa, India, we reviewed relevant literature and data, addressed gaps in knowledge, and identified priorities and strategies for future research in India.

DISCUSSION

The scope of the problem in India is enormous, based on the potential for climate change and variability to exacerbate endemic malaria, dengue, yellow fever, cholera, and chikungunya, as well as chronic diseases, particularly among the millions of people who already experience poor sanitation, pollution, malnutrition, and a shortage of drinking water. Ongoing efforts to study these risks were discussed but remain scant. A universal theme of the recommendations developed was the importance of improving the surveillance, monitoring, and integration of meteorological, environmental, geospatial, and health data while working in parallel to implement adaptation strategies.

CONCLUSIONS

It will be critical for India to invest in improvements in information infrastructure that are innovative and that promote interdisciplinary collaborations while embarking on adaptation strategies. This will require unprecedented levels of collaboration across diverse institutions in India and abroad. The data can be used in research on the likely impacts of climate change on health that reflect India's diverse climates and populations. Local human and technical capacities for risk communication and promoting adaptive behavior must also be enhanced.

Forcing versus feedback: epidemic malaria and monsoon rains in northwest India

Malaria epidemics in regions with seasonal windows of transmission can vary greatly in size from year to year. A central question has been whether these interannual cycles are driven by climate, are instead generated by the intrinsic dynamics of the disease, or result from the resonance of these two mechanisms. This corresponds to the more general inverse problem of identifying the respective roles of external forcings vs. internal feedbacks from time series for nonlinear and noisy systems. We propose here a quantitative approach to formally compare rival hypotheses on climate vs. disease dynamics, or external forcings vs. internal feedbacks, that combines dynamical models with recently developed, computational inference methods. The interannual patterns of epidemic malaria are investigated here for desert regions of northwest India, with extensive epidemiological records for Plasmodium falciparum malaria for the past two decades. We formulate a dynamical model of malaria transmission that explicitly incorporates rainfall, and we rely on recent advances on parameter estimation for nonlinear and stochastic dynamical systems based on sequential Monte Carlo methods. Results show a significant effect of rainfall in the inter-annual variability of epidemic malaria that involves a threshold in the disease response. The model exhibits high prediction skill for yearly cases in the malaria transmission season following the monsoonal rains. Consideration of a more complex model with clinical immunity demonstrates the robustness of the findings and suggests a role of infected individuals that lack clinical symptoms as a reservoir for transmission. Our results indicate that the nonlinear dynamics of the disease itself play a role at the seasonal, but not the interannual, time scales. They illustrate the feasibility of forecasting malaria epidemics in desert and semi-arid regions of India based on climate variability. This approach should be applicable to malaria in other locations, to other infectious diseases, and to other nonlinear systems under forcing.

Malaria epidemics can exhibit pronounced variation from year to year that can be driven by external forcings, such as climate, or can be generated instead by dynamic feedbacks within the disease system itself. For example, levels of immunity in the population (or control efforts) can rise and fall as the result of past levels of infection. This type of feedback is found in the dynamics of all (nonlinear) biological systems. Feedbacks can interact in complex ways with external drivers, for example by creating refractory periods. It remains a challenge to identify internal feedbacks vs. external forcings from available temporal records of aggregated reported cases and forcing variables. We propose a quantitative approach that can statistically compare the hypotheses of feedbacks vs. forcings (epidemiological vs. climate) based on dynamical and mechanistic models. Our approach is computational, based on a large number of computer simulations of the different models. We illustrate and apply the approach to the analysis of extensive monthly records for malaria incidence in desert regions of India that span two decades. Our analyses confirm the strong role of rainfall, and quantify this effect with transmission model(s) for malaria that include rainfall and are shown to exhibit a remarkable prediction skill.

Association of early annual peak influenza activity with El Niño southern oscillation in Japan

Background  Seasonality characterizing influenza epidemics suggests susceptibility to climate variation. El Niño southern oscillation (ENSO), which involves two extreme events, El Niño and La Niña, is well‐known for its large effects on inter‐annual climate variability. The influence of ENSO on several diseases has been described.

Objectives  In this study, we attempt to analyze the possible influence of ENSO on the timing of the annual influenza activity peak using influenza‐like illness report data in Japan during 1983–2007.

Materials  Influenza surveillance data for 25 influenza epidemics, available under the National Epidemiological Surveillance of the Infectious Diseases, was used in this study. ENSO data were obtained from the Japan Meteorological Agency.

Results  Influenza‐like illness peak week varied largely during the study period, ranging between 4th and 11th weeks (middle of winter to early spring). The average of peak week during ENSO cycles (n = 11, average = 4·5 ± 0·9) was significantly earlier than in non‐ENSO years (n = 14, average = 7·6 ± 2·9; P = 0·01), but there was no significant difference in the peak timing between hot (El Niño) and cold (La Niña) phases. Earlier peaks of influenza activity were observed in 16, out of 25, epidemics. These coincided with 10 (90·9%) out of 11 ENSO and 6 (85·7%) out of seven large‐scale epidemics.

Conclusion  Influenza activity peak occurred earlier in years associated with ENSO and/or large scale epidemics.

Climate change and malaria in Canada: a systems approach

This article examines the potential for changes in imported and autochthonous malaria incidence in Canada as a consequence of climate change. Drawing on a systems framework, we qualitatively characterize and assess the potential direct and indirect impact of climate change on malaria in Canada within the context of other concurrent ecological and social trends. Competent malaria vectors currently exist in southern Canada, including within this range several major urban centres, and conditions here have historically supported endemic malaria transmission. Climate change will increase the occurrence of temperature conditions suitable for malaria transmission in Canada, which, combined with trends in international travel, immigration, drug resistance, and inexperience in both clinical and laboratory diagnosis, may increase malaria incidence in Canada and permit sporadic autochthonous cases. This conclusion challenges the general assumption of negligible malaria risk in Canada with climate change.

Therapeutic responses of Plasmodium vivax and P. falciparum to chloroquine, in an area of western India where P. vivax predominates

In 2003-2005, following an increase in the local incidence of human malaria, the therapeutic efficacy of chloroquine (CQ) in the treatment of Plasmodium vivax and P. falciparum malaria was evaluated in the Anand district of Gujarat state, in western India. After oral administration of CQ, clinical and parasitological responses were measured over a follow-up period of 28 days, following the standard protocol of the World Health Organization. Most of the recurrent infections were checked, by genotyping, to see whether they were the result of treatment failure or re-infection during the follow-up. At the primary health centre (PHC) in Deva, all 57 P. vivax cases included in the study responded to CQ within 3 days. At the Pansora PHC, however, only 59 [90.8%, with a 95% confidence interval (CI) of 83.7%-97.8%] of the 65 P. vivax cases appeared to respond completely, recurrent infections being observed in the other six cases (9.2%; CI=2.2%-16.3%). Of the four recurrent infections checked by genotyping, however, only two appeared to be the result of true treatment failure. Twenty-seven (81.8%; CI=67.2%-94.4%) of the 33 P. falciparum cases who were enrolled in the study, all from Pansora PHC also showed apparent treatment failure, with one early failure, 17 late clinical failures and nine late parasitological failures. All 23 P. falciparum cases that showed apparent treatment failure and were investigated by genotyping appeared to be true cases of failure, none showing any evidence of re-infection during follow-up. The mean parasite-clearance times for those infected with P. falciparum, both those considered CQ-sensitive and the treatment failures, exceeded 2 days. These results indicate the presence of CQ-resistant P. vivax and P. falciparum in Anand district. The high frequency of CQ failure against P. falciparum observed in this study led to a change in the drug policy at the Pansora PHC, with artemisinin-based combination therapy now being used for the first-line treatment of P. falciparum malaria. Chloroquine remains the recommended first-line treatment for P. vivax infections in the area but the treatment failure seen in at least two P. vivax cases indicates a need for further monitoring of the therapeutic efficacy of CQ against such infections, in central Gujarat and elsewhere.

El Niño Southern Oscillation (ENSO) and annual malaria incidence in Southern Africa

We evaluated the association between annual malaria incidence and El Niño Southern Oscillation (ENSO) as measured by the Southern Oscillation Index (SOI) in five countries in Southern Africa from 1988 to 1999. Below normal incidence of malaria synchronised with a negative SOI (El Niño) and above normal incidence with a positive SOI (La Niña), which lead to dry and wet weather conditions, respectively. In most countries there was a positive relationship between SOI and annual malaria incidence, especially where Anopheles arabiensis is a major vector. This mosquito breeds in temporary rain pools and is highly sensitive to fluctuations in weather conditions. South Africa and Swaziland have the most reliable data and showed the strongest associations, but the picture there may also be compounded by the moderating effect of other oscillatory systems in the Indian Ocean. The impact of ENSO also varies over time within countries, depending on existing malaria control efforts and response capacity. There remains a need for quantitative studies that at the same time consider both ENSO-driven climate anomalies and non-ENSO factors influencing epidemic risk potential to assess their relative importance in order to provide an empirical basis for malaria epidemic forecasting models.

The changing dynamics of Plasmodium vivax and P. falciparum in central India: trends over a 27-year period (1975--2002)

The changing epidemiology of malaria since 1975 was studied in a tribal forested belt of central India, Chhattisgarh state, which is the second most highly malarious state in India. Chhattisgarh, which accounts for 2% of the total population of the country, contributed >16% of the total malaria cases, 23% of Plasmodium falciparum, and 7% of deaths due to malaria in the country. Retrospective analysis further revealed that, in 1975--76, P. vivax was the predominant species (58%); however, since 1979, P. falciparum showed a steady upward trend (50%), and in 2002. P. vivax reduced to 28%. Between 1986 and 2000, P. falciparum cases reported by the National Anti Malaria Programme have increased 500%, and the number of deaths also showed a similar alarming increase. From 2000 to 2002, though the number of malaria infections and number of deaths declined sharply as a result of intensive intervention measures (30% and 95%, respectively), which included new drugs like Sulfadoxine Pyrimethamine and Arteether under Enhanced Malaria Control Programme, the proportion of P. falciparum has held steady without any decline. Moreover, along with Anopheles fluviatilis, the traditional vector in the forest, An. culicifacies has also established itself in the forest. The comeback of malaria and establishment of new vectors was largely due to the deterioration of health services along with emergence of resistance in P. falciparum to Chloroquine and in An. culicifacies to DDT. Therefore, a more diversified malaria control program might be needed for sustainable malaria control.

Association of influenza epidemics with global climate variability

The reasons for the seasonality and annual changes in the impact of influenza epidemics remain poorly understood. We investigated the covariations between a major component of climate, namely the El Niño Southern Oscillation (ENSO), and indicators of the impact of influenza, as measured by morbidity, excess mortality and viral subtypes collected in France during the period 1971-2002. We show that both the circulating subtype and the magnitude of ENSO are associated with the impact of influenza epidemics. Recognition of this association could lead to better understanding of the mechanisms of emergence of influenza epidemics.

The burden of malaria in Ahmedabad city, India: a retrospective analysis of reported cases and deaths

Owing to the paucity of accurate information on the burden of malaria in urban India, a retrospective, epidemiological study was carried out in Ahmedabad city, which has a population of about 3 million. Surveillance data for the years 1965-1998 showed a gradual resurgence of malaria between 1967 to 1976, followed by waves of low and high incidences. Plasmodium vivax always predominated but the proportion of cases attributed to P. falciparum increased markedly from 1983. When the surveillance data and health records of the major public and private health facilities in the city were analysed, for the period between 1991 and 1998, P. vivax was found to account for 69% of all malaria cases and P. falciparum for the other 31%. The incidence of infection with each Plasmodium species showed seasonal variation, with that of P. vivax increasing from January to September but then declining as the incidence of P. falciparum increased. The age-specific differences seen in incidence were not statistically significant (P=0.7). The annual numbers of malaria-attributable deaths were strongly correlated with the incidence of P. falciparum (r=0.88). The malaria incidence detected (37431 cases, representing a mean annual incidence of 12.2 cases/1000) was nine times greater than that officially reported (4119 cases, or 1.3 cases/1000 each year). Similarly, the annual malaria-attributable mortality detected (22 deaths/million) was far higher than that officially notified (0.3 death/million). The results of the retrospective analysis not only provide a more accurate, baseline estimate of the burden of malaria in an urban area of India but also clearly indicate the need for a much more efficient health-information system, for recording and managing malaria in such a setting.

El Niño and health

El Niño Southern Oscillation (ENSO) is a climate event that originates in the Pacific Ocean but has wide-ranging consequences for weather around the world, and is especially associated with droughts and floods. The irregular occurrence of El Niño and La Niña events has implications for public health. On a global scale, the human effect of natural disasters increases during El Niño. The effect of ENSO on cholera risk in Bangladesh, and malaria epidemics in parts of South Asia and South America has been well established. The strongest evidence for an association between ENSO and disease is provided by time-series analysis with data series that include more than one event. Evidence for ENSO's effect on other mosquito-borne and rodent-borne diseases is weaker than that for malaria and cholera. Health planners are used to dealing with spatial risk concepts but have little experience with temporal risk management. ENSO and seasonal climate forecasts might offer the opportunity to target scarce resources for epidemic control and disaster preparedness.

The impact of climate change on child health

Human activity has contributed to climate change. The relationship between climate and child health has not been well investigated. This review discusses the role of climate change on child health and suggests 3 ways in which this relationship may manifest. First, environmental changes associated with anthropogenic greenhouse gases can lead to respiratory diseases, sunburn, melanoma, and immunosuppression. Second, climate change may directly cause heat stroke, drowning, gastrointestinal diseases, and psychosocial maldevelopment. Third, ecologic alterations triggered by climate change can increase rates of malnutrition, allergies and exposure to mycotoxins, vector-borne diseases (malaria, dengue, encephalitides, Lyme disease), and emerging infectious diseases. Further climate change is likely, given global industrial and political realities. Proactive and preventive physician action, research focused on the differential effects of climate change on subpopulations including children, and policy advocacy on the individual and federal levels could contain climate change and inform appropriate prevention and response.

Patterns of rainfall and malaria in Madhya Pradesh, central India

Some recent outbreaks of Plasmodium falciparum malaria have been attributed, at least in part, to increases in the intensity and duration of rainfall caused by the El Niño southern oscillation (ENSO), a periodic climatic phenomenon. Since it takes time for unusually heavy rainfall to translate into unusually high densities of the vector mosquitoes, it has been suggested that data on recent rainfall might be used to predict climate-related epidemics of malaria. This possibility was explored by comparing the patterns in the incidence of malaria in (1) Dungaria, a highly malarious village in the central-Indian district of Mandla, and (2) Mandla district as a whole, for the periods 1986-2000 and 1967-2000, respectively, with data on rainfall for the same areas and periods. Unfortunately, no clear relationship was observed between rainfall and malaria incidence, although a major development project to improve water resources in the study area (which resulted in local villages being partially or completely submerged in water) may have masked any significant association. A useful method for predicting which years are going to be high- or low-risk years for malaria epidemics, in the present and other epidemiological settings, remains a future goal.

Environmental, cultural and social changes and their influence on parasite infections

The changes taking place within the societies, cultures and the environments in which we live are massive and complex. By referring to simple epidemiological models it is possible to build an objective framework with which to look at these changes in terms of their likely impact on the epidemiology of parasitic diseases within human communities. These parameters are listed for hosts and both micro- and macroparasites, as are epidemiologically significant cultural, social and environmental variables. Changes in these variables may be either detrimental or beneficial to human health and may, in addition, interact in complex ways. Examples of the complexity of changes which can influence epidemiology are provided for a cultural template of the population living in the north-east of Thailand.

Climate variability and change in the United States: potential impacts on vector- and rodent-borne diseases

Diseases such as plague, typhus, malaria, yellow fever, and dengue fever, transmitted between humans by blood-feeding arthropods, were once common in the United States. Many of these diseases are no longer present, mainly because of changes in land use, agricultural methods, residential patterns, human behavior, and vector control. However, diseases that may be transmitted to humans from wild birds or mammals (zoonoses) continue to circulate in nature in many parts of the country. Most vector-borne diseases exhibit a distinct seasonal pattern, which clearly suggests that they are weather sensitive. Rainfall, temperature, and other weather variables affect in many ways both the vectors and the pathogens they transmit. For example, high temperatures can increase or reduce survival rate, depending on the vector, its behavior, ecology, and many other factors. Thus, the probability of transmission may or may not be increased by higher temperatures. The tremendous growth in international travel increases the risk of importation of vector-borne diseases, some of which can be transmitted locally under suitable circumstances at the right time of the year. But demographic and sociologic factors also play a critical role in determining disease incidence, and it is unlikely that these diseases will cause major epidemics in the United States if the public health infrastructure is maintained and improved.

The effects of changing weather on public health

Many diseases are influenced by weather conditions or display strong seasonality, suggestive of a possible climatic contribution. Projections of future climate change have, therefore, compelled health scientists to re-examine weather/disease relationships. There are three projected physical consequences of climate change: temperature rise, sea level rise, and extremes in the hydrologic cycle. This century, the Earth has warmed by about 0.5 degrees centigrade, and the mid-range estimates of future temperature change and sea level rise are 2.0 degrees centigrade and 49 centimeters, respectively, by the year 2100. Extreme weather variability associated with climate change may especially add an important new stress to developing nations that are already vulnerable as a result of environmental degradation, resource depletion, overpopulation, or location (e.g. low-lying coastal deltas). The regional impacts of climate change will vary widely depending on existing population vulnerability. Health outcomes of climate change can be grouped into those of: (a) direct physical consequences, e.g. heat mortality or drowning; (b) physical/chemical sequelae, e.g. atmospheric transport and formation of air pollutants; (c) physical/biological consequences, e.g. response of vector- and waterborne diseases, and food production; and (d) sociodemographic impacts, e.g. climate or environmentally induced migration or population dislocation. Better understanding of the linkages between climate variability as a determinant of disease will be important, among other key factors, in constructing predictive models to guide public health prevention.

Effects of environmental change on emerging parasitic diseases

Ecological disturbances exert an influence on the emergence and proliferation of malaria and zoonotic parasitic diseases, including, Leishmaniasis, cryptosporidiosis, giardiasis, trypanosomiasis, schistosomiasis, filariasis, onchocerciasis, and loiasis. Each environmental change, whether occurring as a natural phenomenon or through human intervention, changes the ecological balance and context within which disease hosts or vectors and parasites breed, develop, and transmit disease. Each species occupies a particular ecological niche and vector species sub-populations are distinct behaviourally and genetically as they adapt to man-made environments. Most zoonotic parasites display three distinct life cycles: sylvatic, zoonotic, and anthroponotic. In adapting to changed environmental conditions, including reduced non-human population and increased human population, some vectors display conversion from a primarily zoophyllic to primarily anthrophyllic orientation. Deforestation and ensuing changes in landuse, human settlement, commercial development, road construction, water control systems (dams, canals, irrigation systems, reservoirs), and climate, singly, and in combination have been accompanied by global increases in morbidity and mortality from emergent parasitic disease. The replacement of forests with crop farming, ranching, and raising small animals can create supportive habitats for parasites and their host vectors. When the land use of deforested areas changes, the pattern of human settlement is altered and habitat fragmentation may provide opportunities for exchange and transmission of parasites to the heretofore uninfected humans. Construction of water control projects can lead to shifts in such vector populations as snails and mosquitoes and their parasites. Construction of roads in previously inaccessible forested areas can lead to erosion, and stagnant ponds by blocking the flow of streams when the water rises during the rainy season. The combined effects of environmentally detrimental changes in local land use and alterations in global climate disrupt the natural ecosystem and can increase the risk of transmission of parasitic diseases to the human population.

Etiology of interepidemic periods of mosquito-borne disease

Dengue viruses and malaria protozoa are of increasing global concern in public health. The diseases caused by these pathogens often show regular seasonal patterns in incidence because of the sensitivity of their mosquito vectors to climate. Between years in endemic areas, however, there can be further significant variation in case numbers for which public health systems are generally unprepared. There is an acute need for reliable predictions of within-year and between-year epidemic events. The prerequisite for developing any system of early warning is a detailed understanding of the factors involved in epidemic genesis. In this report we discuss the potential causes of the interepidemic periods in dengue hemorrhagic fever in Bangkok and of Plasmodium falciparum malaria in a highland area of western Kenya. The alternative causes are distinguished by a retrospective analysis of two unique and contemporaneous 33-year time series of epidemiological and associated meteorological data recorded at these two sites. We conclude that intrinsic population dynamics offer the most parsimonious explanation for the observed interepidemic periods of disease in these locations.

Deriving meteorological variables across Africa for the study and control of vector-borne disease: a comparison of remote sensing and spatial interpolation of climate

This paper presents the results of an investigation into the utility of remote sensing (RS) using meteorological satellites sensors and spatial interpolation (SI) of data from meteorological stations, for the prediction of spatial variation in monthly climate across continental Africa in 1990. Information from the Advanced Very High Resolution Radiometer (AVHRR) of the National Oceanic and Atmospheric Administration's (NOAA) polar-orbiting meteorological satellites was used to estimate land surface temperature (LST) and atmospheric moisture. Cold cloud duration (CCD) data derived from the High Resolution Radiometer (HRR) on-board the European Meteorological Satellite programme's (EUMETSAT) Meteosat satellite series were also used as a RS proxy measurement of rainfall. Temperature, atmospheric moisture and rainfall surfaces were independently derived from SI of measurements from the World Meteorological Organization (WMO) member stations of Africa. These meteorological station data were then used to test the accuracy of each methodology, so that the appropriateness of the two techniques for epidemiological research could be compared. SI was a more accurate predictor of temperature, whereas RS provided a better surrogate for rainfall; both were equally accurate at predicting atmospheric moisture. The implications of these results for mapping short and long-term climate change and hence their potential for the study and control of disease vectors are considered. Taking into account logistic and analytical problems, there were no clear conclusions regarding the optimality of either technique, but there was considerable potential for synergy.

Predicting key malaria transmission factors, biting and entomological inoculation rates, using modelled soil moisture in Kenya

While malaria transmission varies seasonally, large inter-annual heterogeneity of malaria incidence occurs. Variability in entomological parameters, biting rates and entomological inoculation rates (EIR) have been strongly associated with attack rates in children. The goal of this study was to assess the weather's impact on weekly biting and EIR in the endemic area of Kisian, Kenya. Entomological data collected by the U.S. Army from March 1986 through June 1988 at Kisian, Kenya was analysed with concurrent weather data from nearby Kisumu airport. A soil moisture model of surface-water availability was used to combine multiple weather parameters with landcover and soil features to improve disease prediction. Modelling soil moisture substantially improved prediction of biting rates compared to rainfall; soil moisture lagged two weeks explained up to 45% of An. gambiae biting variability, compared to 8% for raw precipitation. For An. funestus, soil moisture explained 32% variability, peaking after a 4-week lag. The interspecies difference in response to soil moisture was significant (P < 0.00001). A satellite normalized differential vegetation index (NDVI) of the study site yielded a similar correlation (r = 0.42 An. gambiae). Modelled soil moisture accounted for up to 56% variability of An. gambiae EIR, peaking at a lag of six weeks. The relationship between temperature and An. gambiae biting rates was less robust; maximum temperature r2 = -0.20, and minimum temperature r2 = 0.12 after lagging one week. Benefits of hydrological modelling are compared to raw weather parameters and to satellite NDVI. These findings can improve both current malaria risk assessments and those based on El Niño forecasts or global climate change model projections.

An increase in hookworm infection temporally associated with ecologic change

This report describes a significant increase in the prevalence of hookworm infection in an area of Haiti where intestinal parasites are common, but hookworm has not been common. Changing environmental conditions, specifically deforestation and subsequent silting of a local river, have caused periodic flooding with deposition of a layer of sandy loam topsoil and increased soil moisture. We speculate that these conditions, conducive to transmission of the infection, have allowed hookworm to reemerge as an important human pathogen.

The El Niño Southern Oscillation and the historic malaria epidemics on the Indian subcontinent and Sri Lanka: an early warning system for future epidemics?

The recurrent great malaria epidemics which occurred in the Punjab province of former British India and Ceylon before the introduction of residual insecticides have been related to excessive and failing monsoon rains respectively. In the arid Punjab, rainfall facilitated breeding and increased the lifespan of the mosquito vector and, in the wet part of Ceylon, failing monsoon rains caused rivers to pool, creating more favourable breeding conditions. The periodic fluctuations in monsoon rainfall and epidemic malaria are here explained in relation to the El Niño Southern Oscillation. In the Punjab, epidemic malaria between 1868 and 1943 correlates significantly (r = 0.34, P < 0.005) with the sea surface temperature anomalies in the Eastern Equatorial Pacific, a parameter of the oscillation, and epidemics were significantly more prevalent in a year with a wet monsoon following a dry El Niño year than in other years. In Ceylon, epidemics were significantly more prevalent during El Niño years, when the same south-west monsoon tends to fail. With the reduced reliance on residual insecticides and the recurrence of epidemic malaria on the Indian subcontinent, advances made in predicting El Niño events may be used to forecast high and low risk years for future malaria epidemics.