Predicting high-risk years for malaria in Colombia using parameters of El Niño Southern Oscillation

Environmental and socio-economic determinants of the occurrence of malaria clusters in Colombia

This study identifies the environmental and socio-economic determinants of clusters of high malaria incidence in Colombia during the period of 2008-2019. The malaria cases were obtained from the National System of Surveillance in Public Health, with 798,897 cases reported in the 986 Colombian municipalities evaluated during the study period. Spatial autocorrelation of incidence was examined with global and local indices. Clusters were identified in the Amazon, Pacific, and Uraba-Bajo Cauca-Alto Sinú regions. The factors associated with a municipality belonging to a high-incidence cluster were identified using a logistic regression model with mixed effects and showed a positive association for the variables (forest coverage and minimum multi-year average rainfall). An inverse relationship was observed for aqueduct coverage and the odds of belonging to a cluster. A 1% increase in forest coverage was associated with a 4.2% increase in the odds of belonging to a malaria cluster. The association with minimum multi-year average rainfall was positive (OR = 1.0011; 95% CI 1.0005-1.0027). A 1% increase in aqueduct coverage was associated with a 4.3% decrease in the odds of belonging to malaria cluster. The identification of malaria cluster determinants in Colombia could help guide surveillance and disease control policies.

Projecting Malaria Incidence Based on Climate Change Modeling Approach: A Systematic Review

BACKGROUND: Climate change will affect the transmission of malaria by shifting the geographical space of the vector. AIM: The review aims to examine the climate change modeling approach and climatic variables used for malaria projection. METHODS: Articles were systematically searched from four databases, Scopus, Web of Science, PubMed, and SAGE. The PICO concept was used for formulation search and PRISMA approach to identify the final articles. RESULTS: A total of 27 articles were retrieved and reviewed. There were six climate factors identified in this review: Temperature, rainfall/precipitation, humidity, wind, solar radiation, and climate change scenarios. Modeling approaches used to project future malarial trend includes mathematical and computational approach. CONCLUSION: This review provides robust evidence of an association between the impact of climate change and malaria incidence. Prediction on seasonal patterns would be useful for malaria surveillance in public health prevention and mitigation strategies.

Spatiotemporal dynamics of dengue in Colombia in relation to the combined effects of local climate and ENSO

Dengue virus (DENV) is an endemic disease in the hot and humid low-lands of Colombia. We characterize the association of monthly series of dengue cases with indices of El Niño/Southern Oscillation (ENSO) at the tropical Pacific and local climatic variables in Colombia during the period 2007-2017 at different temporal and spatial scales. For estimation purposes, we use lagged cross-correlations (Pearson test), cross-wavelet analysis (wavelet cross spectrum, and wavelet coherence), as well as a novel nonlinear causality method, PCMCI, that allows identifying common causal drivers and links among high dimensional simultaneous and time-lagged variables. Our results evidence the strong association of DENV cases in Colombia with ENSO indices and with local temperature and rainfall. El Niño (La Niña) phenomenon is related to an increase (decrease) of dengue cases nationally and in most regions and departments, with maximum correlations occurring at shorter time lags in the Pacific and Andes regions, closer to the Pacific Ocean. This association is mainly explained by the ENSO-driven increase in temperature and decrease in rainfall, especially in the Andes and Pacific regions. The influence of ENSO is not stationary, given the reduction of DENV cases since 2005, and that local climate variables vary in space and time, which prevents to extrapolate results from one region to another. The association between DENV and ENSO varies at national and regional scales when data are disaggregated by seasons, being stronger in DJF and weaker in SON. Overall, the Pacific and Andes regions control the relationship between dengue dynamics and ENSO at national scale. Cross-wavelet analysis indicates that the ENSO-DENV relation in Colombia exhibits a strong coherence in the 12 to 16-months frequency band, which implies the frequency locking between the annual cycle and the interannual (ENSO) timescales. Results of nonlinear causality metrics reveal the complex concomitant effects of ENSO and local climate variables, while offering new insights to develop early warning systems for DENV in Colombia.

Seasonal distribution and environmental parameters associated with Brugia pahangi and Dirofilaria immitis in naturally infected dogs in Bangkok and vicinity, Thailand

Dirofilaria immitis and Brugia pahangi are vector-borne parasites found in dogs and cats, including Thailand. In order to evaluate the effects of season and environmental parameters on the prevalence of these parasites, this retrospective study was conducted in 2019. A total of 79,506 canine blood samples were examined. B. pahangi was found in 0.55% of samples (438/79,506; 95% CI 0.50–0.61) while D. immitis was detected in 0.43% (345/79,506; 95% CI 0.39–0.48). One-way ANOVA found no effect of seasonal conditions on prevalence. For B. pahangi, the parameters rainfall, relative humidity and sunshine hours showed associations with p ≤ 0.20 and were included in multiple logistic regressions resulting in adjusted odds ratios of 0.53, 1.31 and 0.55, respectively. For D. immitis, only average temperature showed p ≤ 0.20, resulting in an odds ratio of 0.42. In conclusion, Thailand has environmental parameters that do not change very much during the year, so they might not affect the prevalence of two filarial nematodes. However, the threat of B. pahangi and D. immitis should not be ignored, especially in subtropical regions where their vectors are abundant. Both owners and veterinarians should be concerned about filarial prevention and control of D. immitis and B. pahangi.

Concomitant malaria, dengue and COVID-19: an extraordinary challenge for Colombia's public health system

Malaria and dengue are vector-borne endemic diseases in the low-lying regions of Colombia. Outbreaks of both diseases appear during the occurrence of El Niño in the tropical Pacific. We present updated data confirming the relation, which are explained by the increase in temperature. Malaria shows an increasing trend, of which climate change cannot be disregarded. The migration of over 1?200?000 Venezuelans hiding away from the internal crisis has complicated the situation. Further research is needed to pinpoint the linkages between vector-borne diseases and climate variability, but also with current and future impacts of climate change, and alarming deforestation rates of Colombia. The public health system has been impacted by the COVID-19 pandemic, especially in the poorest and most vulnerable regions (Pacific coast, Amazon and Orinoco). This note constitutes a call to Colombia's public health system to maintain vector and water-borne diseases services, which cannot become neglected amid the COVID-19 pandemic.

Long-term transmission patterns and public health policies leading to malaria elimination in Panamá

Background

The present study provides a countrywide perspective of the malaria situation in Panamá over a long-term framework, with the purpose of identifying historical malaria resurgence events and their potential causes.

Methods

A descriptive-ecological study was conducted by analysing demographic and epidemiological annual malaria time series data in Panamá (1884–2019) using several data sources. Malaria intensity indicators were calculated during the study period. The effects of El Niño Southern Oscillation on malaria transmission were also analysed using a retrospective analysis of malaria cases between 1957 and 2019.

Results

Several factors were identified responsible for malaria resurgence in Panamá, mostly related with Malaria Control Programme weakening. During the past 20 years (2000–2019) malaria has progressively increased in prevalence within indigenous settlements, with a predominance of male cases and a high proportion (15% of total cases) in children less than 5 years old. During this period, a significant and increasing proportion of the Plasmodium falciparum cases were imported. Retrospective analysis (1957–2019) evidenced that ENSO had a significant impact on malaria transmission dynamics in Panamá.

Conclusions

Data analysis confirmed that although authorities have been successful in focalizing malaria transmission in the country, there are still neglected issues to be solved and important intercultural barriers that need to be addressed in order to achieve elimination of the disease by 2022. This information will be useful for targeting strategies by the National Malaria Elimination Programme.

Health policy impacts on malaria transmission in Costa Rica

Costa Rica is near malaria elimination. This achievement has followed shifts in malaria health policy. Here, we evaluate the impacts that different health policies have had on malaria transmission in Costa Rica from 1913 to 2018. We identified regime shifts and used regression models to measure the impact of different health policies on malaria transmission in Costa Rica using annual case records. We found that vector control and prophylactic treatments were associated with a 50% malaria case reduction in 1929-1931 compared with 1913-1928. DDT introduction in 1946 was associated with an increase in annual malaria case reduction from 7.6% (1942-1946) to 26.4% (1947-1952). The 2006 introduction of 7-day supervised chloroquine and primaquine treatments was the most effective health policy between 1957 and 2018, reducing annual malaria cases by 98% (2009-2018) when compared with 1957-1968. We also found that effective malaria reduction policies have been sensitive to natural catastrophes and extreme climatic events, both of which have increased malaria transmission in Costa Rica. Currently, outbreaks follow malaria importation into vulnerable areas of Costa Rica. This highlights the need to timely diagnose and treat malaria, while improving living standards, in the affected areas.

[Seasonality of dengue reporting in state capitals in the Brazilian Amazon and impacts of El Niño/La Niña]

The dynamics of dengue transmission are multifactorial and involve socioeconomic, ecological, and environmental aspects, the latter being closely related to local climatic conditions that affect the vector's reproductive cycle. Climate depends in turn on tropical oceanic mechanisms such as phases of El Niño/La Niña over the Pacific. The study contributes to this discussion and reports on the correlations between the Multivariate ENSO Index (MEI) in the Pacific and the number of reported dengue cases in seven state capitals in the Brazilian Amazon from 2001 to 2012. The study also analyzes the seasonality pattern (quarterly mean values) in dengue cases throughout the region. Evidence that El Niño/La Niña causes a decrease versus increase in the local rainfall pattern is consistent with the lower versus higher number of reported dengue cases in most of the state capitals in the Amazon, a result proven by the statistically significant negative correlations seen in Manaus (Amazonas), São Luís (Maranhão), Belém (Pará) and Palmas (Tocantins). The 12-years means (2001-2012) revealed the presence of pronounced seasonality in dengue incidence in the majority of the state capitals, with sharp peaks from January to March [Rio Branco (Acre), Manaus, Belém and Palmas] and from April to June (São Luís), corresponding to 50-70% of the annual total. State capitals farther north [Boa Vista (Roraima) and Macapá (Amapá)] showed dengue reporting in all quarters of the year, with no pronounced seasonality.

Population Dynamics of Anopheles albimanus (Diptera: Culicidae) at Ipetí-Guna, a Village in a Region Targeted for Malaria Elimination in Panamá

Anopheles albimanus Wiedemann is a major malaria vector in Mesoamerica and the Caribbean whose population dynamics, in response to changing environments, has been relatively poorly studied. Here, we present monthly adult and larvae data collected from May 2016 to December 2017 in Ipetí-Guna, a village within an area targeted for malaria elimination in the República de Panamá. During the study period we collected a total of 1678 Anopheles spp. mosquitoes (1602 adults and 76 larvae). Over 95% of the collected Anopheles spp. mosquitoes were An. albimanus. Using time series analysis techniques, we found that population dynamics of larvae and adults were not significantly correlated with each other at any time lag, though correlations were highest at one month lag between larvae and adults and four months lag between adults and larvae. Larvae population dynamics had cycles of three months and were sensitive to changes in temperature with 5 months lag, while adult abundance was correlated with itself (1 month lag) and with the normalized difference vegetation index (NDVI) with three months lag. A key observation from our study is the absence of both larvae and adults of An. albimanus between January and April from environments associated with Guna population’s daily activities, which suggests this time window could be the best time to implement elimination campaigns aimed at clearing Plasmodium spp. parasites from Guna populations using, for example, mass drug administration.

Malaria intensity in Colombia by regions and populations

Determining the distribution of disease prevalence among heterogeneous populations at the national scale is fundamental for epidemiology and public health. Here, we use a combination of methods (spatial scan statistic, topological data analysis and epidemic profile) to study measurable differences in malaria intensity by regions and populations of Colombia. This study explores three main questions: What are the regions of Colombia where malaria is epidemic? What are the regions and populations in Colombia where malaria is endemic? What associations exist between epidemic outbreaks between regions in Colombia? Plasmodium falciparum is most prevalent in the Pacific Coast, some regions of the Amazon Basin, and some regions of the Magdalena Basin. Plasmodium vivax is the most prevalent parasite in Colombia, particularly in the Northern Amazon Basin, the Caribbean, and municipalities of Sucre, Antioquia and Cordoba. We find an acute peak of malarial infection at 25 years of age. Indigenous and Afrocolombian populations experience endemic malaria (with household transmission). We find that Plasmodium vivax decreased in the most important hotspots, often with moderate urbanization rate, and was re-introduced to locations with moderate but sustained deforestation. Infection by Plasmodium falciparum, on the other hand, steadily increased in incidence in locations where it was introduced in the 2009-2010 generalized epidemic. Our findings suggest that Colombia is entering an unstable transmission state, where rapid decreases in one location of the country are interconnected with rapid increases in other parts of the country.

Climatic fluctuations and malaria transmission dynamics, prior to elimination, in Guna Yala, República de Panamá

BACKGROUND

Malaria has historically been entrenched in indigenous populations of the República de Panamá. This scenario occurs despite the fact that successful methods for malaria elimination were developed during the creation of the Panamá Canal. Today, most malaria cases in the República de Panamá affect the Gunas, an indigenous group, which mainly live in autonomous regions of eastern Panamá. Over recent decades several malaria outbreaks have affected the Gunas, and one hypothesis is that such outbreaks could have been exacerbated by climate change, especially by anomalous weather patterns driven by the EL Niño Southern Oscillation (ENSO).

RESULTS

Monthly malaria cases in Guna Yala (1998-2016) were autocorrelated up to 2 months of lag, likely reflecting parasite transmission cycles between humans and mosquitoes, and cyclically for periods of 4 months that might reflect relapses of Plasmodium vivax, the dominant malaria parasite transmitted in Panamá. Moreover, malaria case number was positively associated (P < 0.05) with rainfall (7 months of lag), and negatively with the El Niño 4 index (15 months of lag) and the Normalized Difference Vegetation Index, NDVI (8 months of lag), the sign and magnitude of these associations likely related to the impacts of weather patterns and vegetation on the ecology of Anopheles albimanus, the main malaria vector in Guna Yala. Interannual cycles, of approximately 4-year periods, in monthly malaria case numbers were associated with the El Niño 4 index, a climatic index associated with weather and vegetation dynamics in Guna Yala at seasonal and interannual time scales.

CONCLUSION

The results showed that ENSO, rainfall and NDVI were associated with the number of malaria cases in Guna Yala during the study period. These results highlight the vulnerability of Guna populations to malaria, an infection sensitive to climate change, and call for further studies about weather impacts on malaria vector ecology, as well as the association of malaria vectors with Gunas paying attention to their socio-economic conditions of poverty and cultural differences as an ethnic minority.

Malaria early warning tool: linking inter-annual climate and malaria variability in northern Guadalcanal, Solomon Islands

BACKGROUND

Malaria control remains a significant challenge in the Solomon Islands. Despite progress made by local malaria control agencies over the past decade, case rates remain high in some areas of the country. Studies from around the world have confirmed important links between climate and malaria transmission. This study focuses on understanding the links between malaria and climate in Guadalcanal, Solomon Islands, with a view towards developing a climate-based monitoring and early warning for periods of enhanced malaria transmission.

METHODS

Climate records were sourced from the Solomon Islands meteorological service (SIMS) and historical malaria case records were sourced from the National Vector-Borne Disease Control Programme (NVBDCP). A declining trend in malaria cases over the last decade associated with improved malaria control was adjusted for. A stepwise regression was performed between climate variables and climate-associated malaria transmission (CMT) at different lag intervals to determine where significant relationships existed. The suitability of these results for use in a three-tiered categorical warning system was then assessed using a Mann-Whitney U test.

RESULTS

Of the climate variables considered, only rainfall had a consistently significant relationship with malaria in North Guadalcanal. Optimal lag intervals were determined for prediction using R² skill scores. A highly significant negative correlation (R = - 0.86, R² = 0.74, p < 0.05, n = 14) was found between October and December rainfall at Honiara and CMT in northern Guadalcanal for the subsequent January-June. This indicates that drier October-December periods are followed by higher malaria transmission periods in January-June. Cross-validation emphasized the suitability of this relationship for forecasting purposes [Formula: see text]  as did Mann-Whitney U test results showing that rainfall below or above specific thresholds was significantly associated with above or below normal malaria transmission, respectively.

CONCLUSION

This study demonstrated that rainfall provides the best predictor of malaria transmission in North Guadalcanal. This relationship is thought to be underpinned by the unique hydrological conditions in northern Guadalcanal which allow sandbars to form across the mouths of estuaries which act to develop or increase stagnant brackish marshes in low rainfall periods. These are ideal habitats for the main mosquito vector, Anopheles farauti. High rainfall accumulations result in the flushing of these habitats, reducing their viability. The results of this study are now being used as the basis of a malaria early warning system which has been jointly implemented by the SIMS, NVBDCP and the Australian Bureau of Meteorology.

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.

Prospects for malaria elimination in Mesoamerica and Hispaniola

Malaria remains endemic in 21 countries of the American continent with an estimated 427,000 cases per year. Approximately 10% of these occur in the Mesoamerican and Caribbean regions. During the last decade, malaria transmission in Mesoamerica showed a decrease of ~85%; whereas, in the Caribbean region, Hispaniola (comprising the Dominican Republic [DR] and Haiti) presented an overall rise in malaria transmission, primarily due to a steady increase in Haiti, while DR experienced a significant transmission decrease in this period.

The significant malaria reduction observed recently in the region prompted the launch of an initiative for Malaria Elimination in Mesoamerica and Hispaniola (EMMIE) with the active involvement of the National Malaria Control Programs (NMCPs) of nine countries, the Regional Coordination Mechanism (RCM) for Mesoamerica, and the Council of Health Ministries of Central America and Dominican Republic (COMISCA). The EMMIE initiative is supported by the Global Fund for Aids, Tuberculosis and Malaria (GFATM) with active participation of multiple partners including Ministries of Health, bilateral and multilateral agencies, as well as research centers. EMMIE’s main goal is to achieve elimination of malaria transmission in the region by 2020. Here we discuss the prospects, challenges, and research needs associated with this initiative that, if successful, could represent a paradigm for other malaria-affected regions.

Malaria in the Americas: trends from 1959 to 2011

Malaria has declined in recent years in countries of the American continents. In 2011, 12 of 21 endemic countries had already met their 2015 Millennium Development Goal. However, this declining trend has not been adequately evaluated. An analysis of the number of cases per 100,000 people (annual parasite index [API]) and the percentage of positive blood slides (slide positivity rate [SPR]) during the period of 1959-2011 in 21 endemic countries was done using the joinpoint regression methodology. During 1960-1979, API and SPR increased significantly and peaked in the 1980s. Since the 1990s, there have been significant declining trends in both API and SPR. Additionally, both Plasmodium vivax and P. falciparum species-specific incidence have declined. With the exception of two countries, such a collectively declining malaria trend was not observed in previous decades. This presents a unique opportunity for the Americas to seriously consider malaria elimination as a final goal.

Impact on human health of climate changes

There is increasing evidence that climate is rapidly changing. These changes, which are mainly driven by the dramatic increase of greenhouse gas emissions from anthropogenic activities, have the potential to affect human health in several ways. These include a global rise in average temperature, an increased frequency of heat waves, of weather events such as hurricanes, cyclones and drought periods, plus an altered distribution of allergens and vector-borne infectious diseases. The cardiopulmonary system and the gastrointestinal tract are particularly vulnerable to the adverse effects of global warming. Moreover, some infectious diseases and their animal vectors are influenced by climate changes, resulting in higher risk of typhus, cholera, malaria, dengue and West Nile virus infection. On the other hand, at mid latitudes warming may reduce the rate of diseases related to cold temperatures (such as pneumonia, bronchitis and arthritis), but these benefits are unlikely to rebalance the risks associated to warming.

Global decline in suitable habitat for Angiostrongylus ( = Parastrongylus) cantonensis: the role of climate change

Climate change is implicated in the alteration of the ranges of species worldwide. Such shifts in species distributions may introduce parasites/pathogens, hosts, and vectors associated with disease to new areas. The parasite Angiostrongylus ( = Parastrongylus) cantonensis is an invasive species that causes eosinophilic meningitis in humans and neurological abnormalities in domestic/wild animals. Although native to southeastern Asia, A. cantonensis has now been reported from more than 30 countries worldwide. Given the health risks, it is important to describe areas with potentially favorable climate for the establishment of A. cantonensis, as well as areas where this pathogen might become established in the future. We used the program Maxent to develop an ecological niche model for A. cantonensis based on 86 localities obtained from published literature. We then modeled areas of potential A. cantonensis distribution as well as areas projected to have suitable climatic conditions under four Representative Concentration Pathways (RCP) scenarios by the 2050s and the 2070s. The best model contained three bioclimatic variables: mean diurnal temperature range, minimum temperature of coldest month and precipitation of warmest quarter. Potentially suitable habitat for A. cantonensis was located worldwide in tropical and subtropical regions. Under all climate change RCP scenarios, the center of the projected distribution shifted away from the equator at a rate of 68–152 km per decade. However, the extent of areas with highly suitable habitat (>50%) declined by 10.66–15.66% by the 2050s and 13.11–16.11% by the 2070s. These results conflict with previous studies, which have generally found that the prevalence of tropical pathogens will increase during the 21st century. Moreover, it is likely that A. cantonensis will continue to expand its current range in the near future due to introductions and host expansion, whereas climate change will reduce the total geographic area of most suitable climatic conditions during the coming decades.

Implementation of malaria dynamic models in municipality level early warning systems in Colombia. Part I: description of study sites

As part of the Integrated National Adaptation Pilot project and the Integrated Surveillance and Control System, the Colombian National Institute of Health is working on the design and implementation of a Malaria Early Warning System framework, supported by seasonal climate forecasting capabilities, weather and environmental monitoring, and malaria statistical and dynamic models. In this report, we provide an overview of the local ecoepidemiologic settings where four malaria process-based mathematical models are currently being implemented at a municipal level. The description includes general characteristics, malaria situation (predominant type of infection, malaria-positive cases data, malaria incidence, and seasonality), entomologic conditions (primary and secondary vectors, mosquito densities, and feeding frequencies), climatic conditions (climatology and long-term trends), key drivers of epidemic outbreaks, and non-climatic factors (populations at risk, control campaigns, and socioeconomic conditions). Selected pilot sites exhibit different ecoepidemiologic settings that must be taken into account in the development of the integrated surveillance and control system.

The periodicity of Plasmodium vivax and Plasmodium falciparum in Venezuela

We investigated the periodicity of Plasmodium vivax and P. falciparum incidence in time-series of malaria data (1990-2010) from three endemic regions in Venezuela. In particular, we determined whether disease epidemics were related to local climate variability and regional climate anomalies such as the El Niño Southern Oscillation (ENSO). Malaria periodicity was found to exhibit unique features in each studied region. Significant multi-annual cycles of 2- to about 6-year periods were identified. The inter-annual variability of malaria cases was coherent with that of SSTs (ENSO), mainly at temporal scales within the 3-6 year periods. Additionally, malaria cases were intensified approximately 1 year after an El Niño event, a pattern that highlights the role of climate inter-annual variability in the epidemic patterns. Rainfall mediated the effect of ENSO on malaria locally. Particularly, rains from the last phase of the season had a critical role in the temporal dynamics of Plasmodium. The malaria-climate relationship was complex and transient, varying in strength with the region and species. By identifying temporal cycles of malaria we have made a first step in predicting high-risk years in Venezuela. Our findings emphasize the importance of analyzing high-resolution spatial-temporal data to better understand malaria transmission dynamics.

Improving the modeling of disease data from the government surveillance system: a case study on malaria in the Brazilian Amazon

The study of the effect of large-scale drivers (e.g., climate) of human diseases typically relies on aggregate disease data collected by the government surveillance network. The usual approach to analyze these data, however, often ignores a) changes in the total number of individuals examined, b) the bias towards symptomatic individuals in routine government surveillance, and; c) the influence that observations can have on disease dynamics. Here, we highlight the consequences of ignoring the problems listed above and develop a novel modeling framework to circumvent them, which is illustrated using simulations and real malaria data. Our simulations reveal that trends in the number of disease cases do not necessarily imply similar trends in infection prevalence or incidence, due to the strong influence of concurrent changes in sampling effort. We also show that ignoring decreases in the pool of infected individuals due to the treatment of part of these individuals can hamper reliable inference on infection incidence. We propose a model that avoids these problems, being a compromise between phenomenological statistical models and mechanistic disease dynamics models; in particular, a cross-validation exercise reveals that it has better out-of-sample predictive performance than both of these alternative models. Our case study in the Brazilian Amazon reveals that infection prevalence was high in 2004–2008 (prevalence of 4% with 95% CI of 3–5%), with outbreaks (prevalence up to 18%) occurring during the dry season of the year. After this period, infection prevalence decreased substantially (0.9% with 95% CI of 0.8–1.1%), which is due to a large reduction in infection incidence (i.e., incidence in 2008–2010 was approximately one fifth of the incidence in 2004–2008).We believe that our approach to modeling government surveillance disease data will be useful to advance current understanding of large-scale drivers of several diseases.

Disease data collected by the government surveillance system are frequently used to understand the influence of large-scale phenomena (e.g., climate) on human health because these data often have a large temporal and/or geographical span. The down side is that a) these data are often biased towards individuals that come to the health facilities (i.e., symptomatic individuals); and b) the number of individuals examined can vary substantially regardless of concurrent changes in prevalence or incidence (e.g., due to shortage of personnel or supplies in health facilities), directly impacting the number of disease cases detected. Current modeling approaches typically ignore these peculiarities of the government data. Furthermore, current approaches do not take into account that observations directly influence disease dynamics since individuals with a positive diagnosis are often subsequently treated for the disease. In this article, we develop a novel model to circumvent these shortcomings and apply it to simulated data, highlighting how inference on infection incidence and prevalence might be misleading when some of the issues mentioned above are ignored. Finally, we illustrate this model using malaria data from the Brazilian Amazon, revealing the strong role of precipitation on infection prevalence seasonality and striking patterns in infection incidence.

Spatial-temporal analysis of malaria and the effect of environmental factors on its incidence in Yongcheng, China, 2006-2010

Background

In 2003, Plasmodium vivax malaria has re-emerged in central eastern China including Yongcheng prefecture, Henan Province, where no case has been reported for eleven years. Our goals were to detect the space-time distribution pattern of malaria and to determine significant environmental variables contributing to malaria incidence in Yongcheng from 2006 to 2010, thus providing scientific basis for further optimizing current malaria surveillance and control programs.

Methods

This study examined the spatial and temporal heterogeneities in the risk of malaria and the influencing factors on malaria incidence using geographical information system (GIS) and time series analysis. Univariate analysis was conducted to estimate the crude correlations between malaria incidence and environmental variables, such as mosquito abundance and climatic factors. Multivariate analysis was implemented to construct predictive models to explore the principal environmental determinants on malaria epidemic using a Generalized Estimating Equation (GEE) approach.

Results

Annual malaria incidence at town-level decreased from the north to south, and monthly incidence at prefecture-level demonstrated a strong seasonal pattern with a peak from July to November. Yearly malaria incidence had a visual spatial association with yearly average temperature. Moreover, the best-fit temporal model (model 2) (QIC = 16.934, P<0.001, R² = 0.818) indicated that significant factors contributing to malaria incidence were maximum temperature at one month lag, average humidity at one month lag, and malaria incidence of the previous month.

Conclusions

Findings supported the effects of environment factors on malaria incidence and indicated that malaria control targets should vary with intensity of malaria incidence, with more public resource allocated to control the source of infections instead of large scale An. sinensis control when malaria incidence was at a low level, which would benefit for optimizing the malaria surveillance project in China and some other countries with unstable or low malaria transmission.

History of malaria research and its contribution to the malaria control success in Suriname: a review

Suriname has cleared malaria from its capital city and coastal areas mainly through the successful use of chloroquine and DDT (dichloro-diphenyl-trichloroethane) during the Global Malaria Eradication programme that started in 1955. Nonetheless, malaria transmission rates remained high in the interior of the country for a long time. An impressive decline in malaria cases was achieved in the past few years, from 14,403 registered cases in 2003 to 1,371 in 2009. The introduction of artemisinin-based combination therapy (ACT) in 2004 has further fuelled the decrease in the number of infections with Plasmodium falciparum. The only population group still heavily burdened with malaria is gold mining industry workers. Interestingly, an important part of malaria cases diagnosed and treated in Suriname originate from border regions. Therefore, practical initiatives of combined efforts between neighbouring countries must be scaled up in order to effectively attack these specific areas. Furthermore, it is of vital importance to keep investing into the malaria control programme and public awareness campaigns. Especially the correct use of ACT must be promoted in order to prevent the emergence of resistance. However, effective preventive measures and adequate therapeutic options are on their own not enough to control, let alone eliminate malaria. Changing personal and social behaviour of people is particularly difficult, but crucial in making the current success sustainable. With this in mind, research on successfully implemented interventions, focusing on behavioural modifications and methods of measuring their effectiveness, must be expanded.

Predictors of local malaria outbreaks: an approach to the development of an early warning system in Colombia

Risk factor surveillance is a complementary tool of morbidity and mortality surveillance that improves the likelihood that public health interventions are implemented in a timely fashion. The aim of this study was to identify population predictors of malaria outbreaks in endemic municipalities of Colombia with the goal of developing an early warning system for malaria outbreaks. We conducted a multiple-group, exploratory, ecological study at the municipal level. Each of the 290 municipalities with endemic malaria that we studied was classified according to the presence or absence of outbreaks. The measurement of variables was based on historic registries and logistic regression was performed to analyse the data. Altitude above sea level [odds ratio (OR) 3.65, 95% confidence interval (CI) 1.34-9.98], variability in rainfall (OR 1.85, 95% CI 1.40-2.44) and the proportion of inhabitants over 45 years of age (OR 0.17, 95% CI 0.08-0.38) were factors associated with malaria outbreaks in Colombian municipalities. The results suggest that environmental and demographic factors could have a significant ability to predict malaria outbreaks on the municipal level in Colombia. To advance the development of an early warning system, it will be necessary to adjust and standardise the collection of required data and to evaluate the accuracy of the forecast models.

The role of El Niño Southern Oscillation (ENSO) on variations of monthly Plasmodium falciparum malaria cases at the Cayenne General Hospital, 1996-2009, French Guiana

BACKGROUND

Malaria remains a serious problem in French Guiana, which is at potential risk for drought linked with the El Niño Event and where there could be a risk of malaria epidemic after the onset of an El Niño event.

METHODS

A time series analysis using ARIMA was developed to investigate temporal correlations between the monthly Plasmodium falciparum case numbers and El Niño Southern Oscillation (ENSO) as measured by the Southern Oscillation Index (SOI) at the Cayenne General Hospital between 1996 and 2009.

RESULTS

The data showed a positive influence of El Niño at a lag of three months on P. falciparum cases (p < 0.001). The incorporation of SOI data in the ARIMA model reduced the AIC by 4%.

CONCLUSIONS

Although there is a statistical link, the predictive value of ENSO to modulate prevention intervention seems marginal in French Guiana. However, additional work should refine the regional dependence of malaria on the ENSO state.

Potential influence of climate change on vector-borne and zoonotic diseases: a review and proposed research plan

BACKGROUND

Because of complex interactions of climate variables at the levels of the pathogen, vector, and host, the potential influence of climate change on vector-borne and zoonotic diseases (VBZDs) is poorly understood and difficult to predict. Climate effects on the nonvector-borne zoonotic diseases are especially obscure and have received scant treatment.

OBJECTIVE

We described known and potential effects of climate change on VBZDs and proposed specific studies to increase our understanding of these effects. The nonvector-borne zoonotic diseases have received scant treatment and are emphasized in this paper.

DATA SOURCES AND SYNTHESIS

We used a review of the existing literature and extrapolations from observations of short-term climate variation to suggest potential impacts of climate change on VBZDs. Using public health priorities on climate change, published by the Centers for Disease Control and Prevention, we developed six specific goals for increasing understanding of the interaction between climate and VBZDs and for improving capacity for predicting climate change effects on incidence and distribution of VBZDs.

CONCLUSIONS

Climate change may affect the incidence of VBZDs through its effect on four principal characteristics of host and vector populations that relate to pathogen transmission to humans: geographic distribution, population density, prevalence of infection by zoonotic pathogens, and the pathogen load in individual hosts and vectors. These mechanisms may interact with each other and with other factors such as anthropogenic disturbance to produce varying effects on pathogen transmission within host and vector populations and to humans. Because climate change effects on most VBZDs act through wildlife hosts and vectors, understanding these effects will require multidisciplinary teams to conduct and interpret ecosystem-based studies of VBZD pathogens in host and vector populations and to identify the hosts, vectors, and pathogens with the greatest potential to affect human populations under climate change scenarios.

Meteorological variables and malaria in a Chinese temperate city: A twenty-year time-series data analysis

OBJECTIVES

This study aimed to examine the impact of climate variation on malaria in a temperate region of China.

METHODS

A 20-year historical time-series data analysis was conducted to examine the relationship between meteorological variables, including maximum and minimum temperatures, rainfall, humidity, and cases of malaria in Jinan, a temperate city in northern China. Data were retrieved from 1959 and 1979 and analyzed on a monthly basis. Spearman correlation and cross-correlation analyses were performed to identify time lag values between each meteorological variable and the number of malaria cases. The Seasonal Autoregressive Integrated Moving Average (SARIMA) model was used to quantify the relationship between the meteorological variables and malaria cases.

RESULTS

The SARIMA models indicate that a 1 degrees C rise in maximum temperature may be related to a 7.7% to 12.7% increase and a 1 degrees C rise in minimum temperature may result in approximately 11.8% to 15.8% increase in the number of malaria cases. A clear association between malaria and other selected weather variables, including rainfall and humidity, has not been detected in this study.

CONCLUSIONS

Temperature could play an important role in the transmission of malaria in temperate regions of China.

Increasing incidence of malaria in the Negro River basin, Brazilian Amazon

Malaria in Brazil is virtually restricted to the Amazon Region, where it has a heterogeneous geographic distribution. We reviewed secondary data in order to describe the regional and temporal distribution of 8018 malaria cases seen between 2003 and 2007 in Santa Isabel do Rio Negro, a municipality in the northwest Brazilian Amazon. A significant rise in malaria incidence, mainly in the Yanomami Indian reservation, was observed during this time. Anopheline breeding sites were also mapped and entomological data were obtained through the capture of larval and adult mosquitoes. Thirty-three potential breeding sites were identified in the urban and periurban areas, 28 of which were positive for anopheline larvae. Anopheles darlingi specimens were captured in both intra- and peridomicile locations in the urban areas. Demographic data were also assessed via a sectional survey, revealing that the majority of dwellings were vulnerable to mosquitoes. This study suggests that urban and periurban areas of this municipality are highly susceptible to epidemic malaria, which is endemic in the Yanomami Indian reservation near the city. In addition, transmission can be perpetuated autochthonously in the urban area, drawing attention to the continuous need for preventative measures such as controlling adult and aquatic stages of mosquitoes and improving housing.

Modelling climate change and malaria transmission

The impact of climate change on human health has received increasing attention in recent years, with potential impacts due to vector-borne diseases only now beginning to be understood. As the most severe vector-borne disease, with one million deaths globally in 2006, malaria is thought most likely to be affected by changes in climate variables due to the sensitivity of its transmission dynamics to environmental conditions. While considerable research has been carried out using statistical models to better assess the relationship between changes in environmental variables and malaria incidence, less progress has been made on developing process-based climate-driven mathematical models with greater explanatory power. Here, we develop a simple model of malaria transmission linked to climate which permits useful insights into the sensitivity of disease transmission to changes in rainfall and temperature variables. Both the impact of changes in the mean values of these key external variables and importantly temporal variation in these values are explored. We show that the development and analysis of such dynamic climate-driven transmission models will be crucial to understanding the rate at which P. falciparum and P. vivax may either infect, expand into or go extinct in populations as local environmental conditions change. Malaria becomes endemic in a population when the basic reproduction number R0 is greater than unity and we identify an optimum climate-driven transmission window for the disease, thus providing a useful indicator for determing how transmission risk may change as climate changes. Overall, our results indicate that considerable work is required to better understand ways in which global malaria incidence and distribution may alter with climate change. In particular, we show that the roles of seasonality, stochasticity and variability in environmental variables, as well as ultimately anthropogenic effects, require further study. The work presented here offers a theoretical framework upon which this future research may be developed.

Climate change and the transmission of vector-borne diseases: a review

This article reviews studies examining the relationship between climate variability and the transmission of vector- and rodent-borne diseases, including malaria, dengue fever, Ross River virus infection, and hemorrhagic fever with renal syndrome. The review has evaluated their study designs, statistical analysis methods, usage of meteorological variables, and results of those studies. The authors found that the limitations of analytical methods exist in most of the articles. Besides climatic variables, few of them have included other factors that can affect the transmission of vector-borne disease (eg, socioeconomic status). In addition, the quantitative relationship between climate and vector-borne diseases is inconsistent. Further research should be conducted among different populations with various climatic/ecological regions by using appropriate statistical models.

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.

The role of ENSO in understanding changes in Colombia's annual malaria burden by region, 1960-2006

BACKGROUND

Malaria remains a serious problem in Colombia. The number of malaria cases is governed by multiple climatic and non-climatic factors. Malaria control policies, and climate controls such as rainfall and temperature variations associated with the El Niño/Southern Oscillation (ENSO), have been associated with malaria case numbers. Using historical climate data and annual malaria case number data from 1960 to 2006, statistical models are developed to isolate the effects of climate in each of Colombia's five contrasting geographical regions.

METHODS

Because year to year climate variability associated with ENSO causes interannual variability in malaria case numbers, while changes in population and institutional control policy result in more gradual trends, the chosen predictors in the models are annual indices of the ENSO state (sea surface temperature [SST] in the tropical Pacific Ocean) and time reference indices keyed to two major malaria trends during the study period. Two models were used: a Poisson and a Negative Binomial regression model. Two ENSO indices, two time reference indices, and one dummy variable are chosen as candidate predictors. The analysis was conducted using the five geographical regions to match the similar aggregation used by the National Institute of Health for its official reports.

RESULTS

The Negative Binomial regression model is found better suited to the malaria cases in Colombia. Both the trend variables and the ENSO measures are significant predictors of malaria case numbers in Colombia as a whole, and in two of the five regions. A one degree Celsius change in SST (indicating a weak to moderate ENSO event) is seen to translate to an approximate 20% increase in malaria cases, holding other variables constant.

CONCLUSION

Regional differentiation in the role of ENSO in understanding changes in Colombia's annual malaria burden during 1960-2006 was found, constituting a new approach to use ENSO as a significant predictor of the malaria cases in Colombia. These results naturally point to additional needed work: (1) refining the regional and seasonal dependence of climate on the ENSO state, and of malaria on the climate variables; (2) incorporating ENSO-related climate variability into dynamic malaria models.

Climate and vectorborne diseases

Climate change could significantly affect vectorborne disease in humans. Temperature, precipitation, humidity, and other climatic factors are known to affect the reproduction, development, behavior, and population dynamics of the arthropod vectors of these diseases. Climate also can affect the development of pathogens in vectors, as well as the population dynamics and ranges of the nonhuman vertebrate reservoirs of many vectorborne diseases. Whether climate changes increase or decrease the incidence of vectorborne diseases in humans will depend not only on the actual climatic conditions but also on local nonclimatic epidemiologic and ecologic factors. Predicting the relative impact of sustained climate change on vectorborne diseases is difficult and will require long-term studies that look not only at the effects of climate change but also at the contributions of other agents of global change such as increased trade and travel, demographic shifts, civil unrest, changes in land use, water availability, and other issues. Adapting to the effects of climate change will require the development of adequate response plans, enhancement of surveillance systems, and development of effective and locally appropriate strategies to control and prevent vectorborne diseases.

Climate change and infectious diseases

The worldwide upturn in the occurrence of both new (emerging) and reemerging or spreading infectious diseases highlights the importance of underlying environmental and social conditions as determinants of the generation, spread, and impact of infectious diseases in human populations. Human ecology is undergoing rapid transition. This encompasses urbanization, rising consumerism, changes in working conditions, population aging, marked increases in mobility, changes in culture and behavior, evolving health-care technologies, and other factors. Global climate change is becoming a further, and major, large-scale influence on the pattern of infectious disease transmission. It is likely to become increasingly important over at least the next halfcentury, as the massive, highinertial, and somewhat unpredictable process of climate change continues. The many ways in which climate change does and will influence infectious diseases are subject to a plethora of modifying influences by other factors and processes: constitutional characteristics of hosts, vectors and pathogens; the prevailing ambient conditions; and coexistent changes in other social, economic, behavioral, and environmental factors. This global anthropogenic process, climate change, along with other unprecedented global environmental changes, is beginning to destabilize and weaken the planet's life-support systems. Infectious diseases, unlike other diseases, depend on the biology and behavior—each often climate-sensitive—of two or more parties. Hence, these diseases will be particularly susceptible to changes as the world's climate and its climate-sensitive geochemical and ecological systems undergo change over the coming decades.

Climate prediction of El Niño malaria epidemics in north-west Tanzania

BACKGROUND

Malaria is a significant public health problem in Tanzania. Approximately 16 million malaria cases are reported every year and 100,000 to 125,000 deaths occur. Although most of Tanzania is endemic to malaria, epidemics occur in the highlands, notably in Kagera, a region that was subject to widespread malaria epidemics in 1997 and 1998. This study examined the relationship between climate and malaria incidence in Kagera with the aim of determining whether seasonal forecasts may assist in predicting malaria epidemics.

METHODS

A regression analysis was performed on retrospective malaria and climatic data during each of the two annual malaria seasons to determine the climatic factors influencing malaria incidence. The ability of the DEMETER seasonal forecasting system in predicting the climatic anomalies associated with malaria epidemics was then assessed for each malaria season.

RESULTS

It was found that malaria incidence is positively correlated with rainfall during the first season (Oct-Mar) (R-squared = 0.73, p < 0.01). For the second season (Apr-Sep), high malaria incidence was associated with increased rainfall, but also with high maximum temperature during the first rainy season (multiple R-squared = 0.79, p < 0.01). The robustness of these statistical models was tested by excluding the two epidemic years from the regression analysis. DEMETER would have been unable to predict the heavy El Niño rains associated with the 1998 epidemic. Nevertheless, this epidemic could still have been predicted using the temperature forecasts alone. The 1997 epidemic could have been predicted from observed temperatures in the preceding season, but the consideration of the rainfall forecasts would have improved the temperature-only forecasts over the remaining years.

CONCLUSION

These results demonstrate the potential of a seasonal forecasting system in the development of a malaria early warning system in Kagera region.

Infectious diseases of severe weather-related and flood-related natural disasters

PURPOSE OF REVIEW

The present review will focus on some of the possible infectious disease consequences of disastrous natural phenomena and severe weather, with a particular emphasis on infections associated with floods and the destruction of infrastructure.

RECENT FINDINGS

The risk of infectious diseases after weather or flood-related natural disasters is often specific to the event itself and is dependent on a number of factors, including the endemicity of specific pathogens in the affected region before the disaster, the type of disaster itself, the impact of the disaster on water and sanitation systems, the availability of shelter, the congregating of displaced persons, the functionality of the surviving public health infrastructure, the availability of healthcare services, and the rapidity, extent, and sustainability of the response after the disaster. Weather events and floods may also impact disease vectors and animal hosts in a complex system.

SUMMARY

Weather or flood-related natural disasters may be associated with an increased risk of soft tissue, respiratory, diarrheal, and vector-borne infectious diseases among survivors and responders.

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.

Oceans and human health: Emerging public health risks in the marine environment

There has been an increasing recognition of the inter-relationship between human health and the oceans. Traditionally, the focus of research and concern has been on the impact of human activities on the oceans, particularly through anthropogenic pollution and the exploitation of marine resources. More recently, there has been recognition of the potential direct impact of the oceans on human health, both detrimental and beneficial. Areas identified include: global change, harmful algal blooms (HABs), microbial and chemical contamination of marine waters and seafood, and marine models and natural products from the seas. It is hoped that through the recognition of the inter-dependence of the health of both humans and the oceans, efforts will be made to restore and preserve the oceans.

Modelling entomological-climatic interactions of Plasmodium falciparum malaria transmission in two Colombian endemic-regions: contributions to a National Malaria Early Warning System

BACKGROUND

Malaria has recently re-emerged as a public health burden in Colombia. Although the problem seems to be climate-driven, there remain significant gaps of knowledge in the understanding of the complexity of malaria transmission, which have motivated attempts to develop a comprehensive model.

METHODS

The mathematical tool was applied to represent Plasmodium falciparum malaria transmission in two endemic-areas. Entomological exogenous variables were estimated through field campaigns and laboratory experiments. Availability of breeding places was included towards representing fluctuations in vector densities. Diverse scenarios, sensitivity analyses and instabilities cases were considered during experimentation-validation process.

RESULTS

Correlation coefficients and mean square errors between observed and modelled incidences reached 0.897-0.668 (P > 0.95) and 0.0002-0.0005, respectively. Temperature became the most relevant climatic parameter driving the final incidence. Accordingly, malaria outbreaks are possible during the favourable epochs following the onset of El Niño warm events. Sporogonic and gonotrophic cycles showed to be the entomological key-variables controlling the transmission potential of mosquitoes' population. Simulation results also showed that seasonality of vector density becomes an important factor towards understanding disease transmission.

CONCLUSION

The model constitutes a promising tool to deepen the understanding of the multiple interactions related to malaria transmission conducive to outbreaks. In the foreseeable future it could be implemented as a tool to diagnose possible dynamical patterns of malaria incidence under several scenarios, as well as a decision-making tool for the early detection and control of outbreaks. The model will be also able to be merged with forecasts of El Niño events to provide a National Malaria Early Warning System.

Spatiotemporal patterns of malaria incidence in northern Thailand

We present a detailed analysis of long-term time series of malaria incidence in northern Thailand. Positive cases for Plasmodium falciparum and P. vivax have been recorded monthly from 1977-2002 at 13 provinces in the region. Time series statistical methods are used to examine the long-term trends and seasonal dynamics of malaria incidence at regional and provincial scales. Both malarial types are declining throughout the region, except in the two provinces that share a large border with Myanmar. The rate of decline in P. vivax has decreased across the region since the end of the 1980s, and this may be a signal of developing resistance or changing vector potential. Both species display a two-peak annual seasonality that may be attributed to patterns of vector occurrence, farming practice and migration of individuals across international borders. In a number of provinces, the importance of the first seasonal peak has grown in recent years, possibly owing to increases in vector densities. The medium-term fluctuations of both species exhibit a clear spatial organisation. There is some evidence of a subtle close to 4-year super annual cycle in P. falciparum, which we suggest is driven by extrinsic factors relating to the climate of the region.

Climate change and human health: present and future risks

There is near unanimous scientific consensus that greenhouse gas emissions generated by human activity will change Earth's climate. The recent (globally averaged) warming by 0.5 degrees C is partly attributable to such anthropogenic emissions. Climate change will affect human health in many ways-mostly adversely. Here, we summarise the epidemiological evidence of how climate variations and trends affect various health outcomes. We assess the little evidence there is that recent global warming has already affected some health outcomes. We review the published estimates of future health effects of climate change over coming decades. Research so far has mostly focused on thermal stress, extreme weather events, and infectious diseases, with some attention to estimates of future regional food yields and hunger prevalence. An emerging broader approach addresses a wider spectrum of health risks due to the social, demographic, and economic disruptions of climate change. Evidence and anticipation of adverse health effects will strengthen the case for pre-emptive policies, and will also guide priorities for planned adaptive strategies.

Control of Human Parasitic Diseases: Context and Overview

The control of parasitic diseases of humans has been undertaken since the aetiology and natural history of the infections was recognized and the deleterious effects on human health and well-being appreciated by policy makers, medical practitioners and public health specialists. However, while some parasitic infections such as malaria have proved difficult to control, as defined by a sustained reduction in incidence, others, particularly helminth infections can be effectively controlled. The different approaches to control from diagnosis, to treatment and cure of the clinically sick patient, to control the transmission within the community by preventative chemotherapy and vector control are outlined. The concepts of eradication, elimination and control are defined and examples of success summarized. Overviews of the health policy and financing environment in which programmes to control or eliminate parasitic diseases are positioned and the development of public-private partnerships as vehicles for product development or access to drugs for parasite disease control are discussed. Failure to sustain control of parasites may be due to development of drug resistance or the failure to implement proven strategies as a result of decreased resources within the health system, decentralization of health management through health-sector reform and the lack of financial and human resources in settings where per capita government expenditure on health may be less than $US 5 per year. However, success has been achieved in several large-scale programmes through sustained national government investment and/or committed donor support. It is also widely accepted that the level of investment in drug development for the parasitic diseases of poor populations is an unattractive option for pharmaceutical companies. The development of partnerships to specifically address this need provides some hope that the intractable problems of the treatment regimens for the trypanosomiases and leishmaniases can be solved in the not too distant future. However, it will be difficult to implement and sustain such interventions in fragile health services often in settings where resources are limited but also in unstable, conflict-affected or post-conflict countries. Emphasis is placed on the importance of co-endemicity and polyparasitism and the opportunity to control parasites susceptible to cost-effective and proven chemotherapeutic interventions for a package of diseases which can be implemented at low cost and which would benefit the poorest and most marginalized groups. The ecology of parasitic diseases is discussed in the context of changing ecology, environment, sociopolitical developments and climate change. These drivers of global change will affect the epidemiology of parasites over the coming decades, while in many of the most endemic and impoverished countries parasitic infections will be accorded lower priority as resourced stressed health systems cope with the burden of the higher-profile killing diseases viz., HIV/AIDS, TB and malaria. There is a need for more holistic thinking about the interactions between parasites and other infections. It is clear that as the prevalence and awareness of HIV has increased, there is a growing recognition of a host of complex interactions that determine disease outcome in individual patients. The competition for resources in the health as well as other social sectors will be a continuing challenge; effective parasite control will be dependent on how such resources are accessed and deployed to effectively address well-defined problems some of which are readily amenable to successful interventions with proven methods. In the health sector, the problems of the HIV/AIDS and TB pandemics and the problem of the emerging burden of chronic non-communicable diseases will be significant competitors for these limited resources as parasitic infections aside from malaria tend to be chronic disabling problems of the poorest who have limited access to scarce health services and are representative of the poorest quintile. Prioritization and advocacy for parasite control in the national and international political environments is the challenge.

East Coast fever and multiple El Niño Southern oscillation ranks

East Coast fever (ECF), a tick-borne disease of cattle, is a major constraint to livestock development in Africa in general and southern Zambia in particular. Understanding the transmission patterns of this disease complex is very difficult as shown by previous studies in southern and eastern Zambia due to the interplay of risk factors. In this long-term study, we investigated whether global weather changes had any influence on disease transmission in traditionally kept cattle in southern Zambia. The results from this study show a strong association between increased Theileria parva contacts in cattle and the presence of El Niño, clearly linking a simple climatic index to disease outbreaks. We therefore propose that in southern Zambia, the simple and readily available multiple El Niño Southern oscillation index (MEI) ranks be used in planning ECF control programmes and early warning.

Laboratory estimation of the effects of increasing temperatures on the duration of gonotrophic cycle of Anopheles albimanus (Diptera: Culicidae)

The increase of malaria transmission in the Pacific Coast of Colombia during the occurrence of El Niño warm event has been found not to be linked to increases in the density of the vector Anopheles albimanus, but to other temperature-sensitive variables such as longevity, duration of the gonotrophic cycle or the sporogonic period of Plasmodium. The present study estimated the effects of temperature on duration of the gonotrophic cycle and on maturation of the ovaries of An. albimanus. Blood fed adult mosquitoes were exposed to temperatures of 24, 27, and 30 degrees C, held individually in oviposition cages and assessed at 12 h intervals. At 24, 27, and 30 degrees C the mean development time of the oocytes was 91.2 h (95% C.I.: 86.5-96), 66.2 h (61.5-70.8), and 73.1 h (64-82.3), respectively. The mean duration of the gonotrophic cycle for these three temperatures was 88.4 h (81.88-94.9), 75 h (71.4-78.7), and 69.1 h (64.6-73.6) respectively. These findings indicate that both parameters in An. albimanus are reduced when temperatures rose from 24 to 30 degrees C, in a nonlinear manner. According to these results the increase in malaria transmission during El Niño in Colombia could be associated with a shortening of the gonotrophic cycle in malaria vectors, which could enhance the frequency of man-vector contact, affecting the incidence of the disease.

Drivers for the emergence and re-emergence of vector-borne protozoal and bacterial diseases

In recent years, vector-borne parasitic and bacterial diseases have emerged or re-emerged in many geographical regions causing global health and economic problems that involve humans, livestock, companion animals and wild life. The ecology and epidemiology of vector-borne diseases are affected by the interrelations between three major factors comprising the pathogen, the host (human, animal or vector) and the environment. Important drivers for the emergence and spread of vector-borne parasites include habitat changes, alterations in water storage and irrigation habits, atmospheric and climate changes, immunosuppression by HIV, pollution, development of insecticide and drug resistance, globalization and the significant increase in international trade, tourism and travel. War and civil unrest, and governmental or global management failure are also major contributors to the spread of infectious diseases. The improvement of epidemic understanding and planning together with the development of new diagnostic molecular techniques in the last few decades have allowed researchers to better diagnose and trace pathogens, their origin and routes of infection, and to develop preventive public health and intervention programs. Health care workers, physicians, veterinarians and biosecurity officers should play a key role in future prevention of vector-borne diseases. A coordinated global approach for the prevention of vector-borne diseases should be implemented by international organizations and governmental agencies in collaboration with research institutions.

Winter North Atlantic Oscillation, temperature and ischaemic heart disease mortality in three English counties

As cold weather is an ischaemic heart disease (IHD) risk factor, year-to-year variations of the level of IHD mortality may be partly determined by inter-annual variations in winter climate. This paper investigates whether there is any association between the level of IHD mortality for three English counties and the winter North Atlantic Oscillation (NAO), which exerts a fundamental control on the nature of the winter climate over Western Europe. Correlation and regression analysis was used to explore the nature of the association between IHD mortality and a climate index (CI) that represents the interaction between the NAO and temperature across England for the winters 1974-1975 to 1989-1999. Statistically significant inverse associations between the CI and the level of IHD mortality were found. Generally, high levels of winter IHD mortality are associated with a negative CI, which represents winters with a strong negative phase of the NAO and anomalously low temperatures across England. Moreover, the nature of the CI in the early stages of winter appears to exert a fundamental control on the general level of winter IHD mortality. Because winter climate is able to explain a good proportion of the inter-annual variability of winter mortality, long-lead forecasting of winter IHD mortality appears to be a possibility. The integration of climate-based health forecasts into decision support tools for advanced general winter emergency service and capacity planning could form the basis of an effective adaptive strategy for coping with the health effects of harsh winters.

Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia II. Weather-based prediction systems perform comparably to early detection systems in identifying times for interventions

BACKGROUND

Timely and accurate information about the onset of malaria epidemics is essential for effective control activities in epidemic-prone regions. Early warning methods that provide earlier alerts (usually by the use of weather variables) may permit control measures to interrupt transmission earlier in the epidemic, perhaps at the expense of some level of accuracy.

METHODS

Expected case numbers were modeled using a Poisson regression with lagged weather factors in a 4th-degree polynomial distributed lag model. For each week, the numbers of malaria cases were predicted using coefficients obtained using all years except that for which the prediction was being made. The effectiveness of alerts generated by the prediction system was compared against that of alerts based on observed cases. The usefulness of the prediction system was evaluated in cold and hot districts.

RESULTS

The system predicts the overall pattern of cases well, yet underestimates the height of the largest peaks. Relative to alerts triggered by observed cases, the alerts triggered by the predicted number of cases performed slightly worse, within 5% of the detection system. The prediction-based alerts were able to prevent 10-25% more cases at a given sensitivity in cold districts than in hot ones.

CONCLUSIONS

The prediction of malaria cases using lagged weather performed well in identifying periods of increased malaria cases. Weather-derived predictions identified epidemics with reasonable accuracy and better timeliness than early detection systems; therefore, the prediction of malarial epidemics using weather is a plausible alternative to early detection systems.

Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia I. Patterns of lagged weather effects reflect biological mechanisms

Background

Malaria epidemics due to Plasmodium falciparum are reported frequently in the East African highlands with high case fatality rates. There have been formal attempts to predict epidemics by the use of climatic variables that are predictors of transmission potential. However, little consensus has emerged about the relative importance and predictive value of different factors. Understanding the reasons for variation is crucial to determining specific and important indicators for epidemic prediction. The impact of temperature on the duration of a mosquito's life cycle and the sporogonic phase of the parasite could explain the inconsistent findings.

Methods

Daily average number of cases was modeled using a robust Poisson regression with rainfall, minimum temperature and maximum temperatures as explanatory variables in a polynomial distributed lag model in 10 districts of Ethiopia. To improve reliability and generalizability within similar climatic conditions, we grouped the districts into two climatic zones, hot and cold.

Results

In cold districts, rainfall was associated with a delayed increase in malaria cases, while the association in the hot districts occurred at relatively shorter lags. In cold districts, minimum temperature was associated with malaria cases with a delayed effect. In hot districts, the effect of minimum temperature was non-significant at most lags, and much of its contribution was relatively immediate.

Conclusions

The interaction between climatic factors and their biological influence on mosquito and parasite life cycle is a key factor in the association between weather and malaria. These factors should be considered in the development of malaria early warning system.

Malaria epidemic early warning and detection in African highlands

Malaria epidemics have long been known to recur in the African highlands. Efforts to develop systems of early warning and detection for epidemics are outlined here with special emphasis on the Highland Malaria Project (HIMAL). This project has been conducting research on the operational implementation of a district-based surveillance and epidemic-monitoring system using a network of sentinel sites in four pilot districts of Kenya and Uganda. The potential use of weather monitoring as well as disease surveillance for effective early warning is being investigated.

Global climate change and the emergence/re-emergence of infectious diseases

Variation in the incidence of vector-borne diseases is associated with extreme weather events and annual changes in weather conditions. Moreover, it is assumed that global warming might lead to an increase of infectious disease outbreaks. While a number of reports link disease outbreaks to single weather events, the El Niño/Southern Oscillation and other large-scale climate fluctuations, no report unequivocally associates vector-borne diseases with increased temperature and the environmental changes expected to accompany it. The complexity of not yet fully understood pathogen transmission dynamics with numerous variables might be an explanation of the problems in assessing the risk factors.