Electronic public health surveillance in developing settings: meeting summary

In some high-income countries, public health surveillance includes systems that use computer and information technology to monitor health data in near-real time, facilitating timely outbreak detection and situational awareness. In September 2007, a meeting convened in Bangkok, Thailand to consider the adaptation of near-real time surveillance methods to developing settings. Thirty-five participants represented Ministries of Health, universities, and militaries in 13 countries, and the World Health Organization (WHO). The keynote presentation by a WHO official underscored the importance of improved national capacity for epidemic surveillance and response under the new International Health Regulations, which entered into force in June 2007. Other speakers presented innovative electronic surveillance systems for outbreak detection and disease reporting in developing countries, and methodologies employed in near-real time surveillance systems in the United States. During facilitated small- and large-group discussion, participants identified key considerations in four areas for adapting near-real time surveillance to developing settings: software, professional networking, training, and data acquisition and processing. This meeting was a first step in extending the benefits of near-real time surveillance to developing settings. Subsequent steps should include identifying funding and partnerships to pilot-test near-real time surveillance methods in developing areas

Developing global climate anomalies suggest potential disease risks for 2006 – 2007

BACKGROUND: El Niño/Southern Oscillation (ENSO) related climate anomalies have been shown to have an impact on infectious disease outbreaks. The Climate Prediction Center of the National Oceanic and Atmospheric Administration (NOAA/CPC) has recently issued an unscheduled El Niño advisory, indicating that warmer than normal sea surface temperatures across the equatorial eastern Pacific may have pronounced impacts on global tropical precipitation patterns extending into the northern hemisphere particularly over North America. Building evidence of the links between ENSO driven climate anomalies and infectious diseases, particularly those transmitted by insects, can allow us to provide improved long range forecasts of an epidemic or epizootic. We describe developing climate anomalies that suggest potential disease risks using satellite generated data. RESULTS: Sea surface temperatures (SSTs) in the equatorial east Pacific ocean have anomalously increased significantly during July – October 2006 indicating the typical development of El Niño conditions. The persistence of these conditions will lead to extremes in global-scale climate anomalies as has been observed during similar conditions in the past. Positive Outgoing Longwave Radiation (OLR) anomalies, indicative of severe drought conditions, have been observed across all of Indonesia, Malaysia and most of the Philippines, which are usually the first areas to experience ENSO-related impacts. This dryness can be expected to continue, on average, for the remainder of 2006 continuing into the early part of 2007. During the period November 2006 – January 2007 climate forecasts indicate that there is a high probability for above normal rainfall in the central and eastern equatorial Pacific Islands, the Korean Peninsula, the U.S. Gulf Coast and Florida, northern South America and equatorial east Africa. Taking into consideration current observations and climate forecast information, indications are that the following regions are at increased risk for disease outbreaks: Indonesia, Malaysia, Thailand and most of the southeast Asia Islands for increased dengue fever transmission and increased respiratory illness; Coastal Peru, Ecuador, Venezuela, and Colombia for increased risk of malaria; Bangladesh and coastal India for elevated risk of cholera; East Africa for increased risk of a Rift Valley fever outbreak and elevated malaria; southwest USA for increased risk for hantavirus pulmonary syndrome and plague; southern California for increased West Nile virus transmission; and northeast Brazil for increased dengue fever and respiratory illness. CONCLUSION: The current development of El Niño conditions has significant implications for global public health. Extremes in climate events with above normal rainfall and flooding in some regions and extended drought periods in other regions will occur. Forecasting disease is critical for timely and efficient planning of operational control programs. In this paper we describe developing global climate anomalies that suggest potential disease risks that will give decision makers additional tools to make rational judgments concerning implementation of disease prevention and mitigation strategies

Differential Susceptibility to Hypertension Is Due to Selection during the Out-of-Africa Expansion

Hypertension is a leading cause of stroke, heart disease, and kidney failure. The genetic basis of blood pressure variation is largely unknown but is likely to involve genes that influence renal salt handling and arterial vessel tone. Here we argue that susceptibility to hypertension is ancestral and that differential susceptibility to hypertension is due to differential exposure to selection pressures during the out-of-Africa expansion. The most important selection pressure was climate, which produced a latitudinal cline in heat adaptation and, therefore, hypertension susceptibility. Consistent with this hypothesis, we show that ecological variables, such as latitude, temperature, and rainfall, explain worldwide variation in heat adaptation as defined by seven functional alleles in five genes involved in blood pressure regulation. The latitudinal cline in heat adaptation is consistent worldwide and is largely unmatched by latitudinal clines in short tandem repeat markers, control single nucleotide polymorphisms, or non-functional single nucleotide polymorphisms within the five genes. In addition, we show that latitude and one of these alleles, GNB3 (G protein β3 subunit) 825T, account for a major portion of worldwide variation in blood pressure. These results suggest that the current epidemic of hypertension is due to exposures of the modern period interacting with ancestral susceptibility. Modern populations differ in susceptibility to these new exposures, however, such that those from hot environments are more susceptible to hypertension than populations from cold environments. This differential susceptibility is likely due to our history of adaptation to climate

The First Prediction of a Rift Valley Fever Outbreak

El Nino/Southern Oscillation (ENSO) related anomalies were analyzed using a combination of satellite measurements of elevated sea surface temperatures, and subsequent elevated rainfall and satellite derived normalized difference vegetation index data. A Rift Valley fever risk mapping model using these climate data predicted areas where outbreaks of Rift Valley fever in humans and animals were expected and occurred in the Horn of Africa from December 2006 to May 2007. The predictions were subsequently confirmed by entomological and epidemiological field investigations of virus activity in the areas identified as at risk. Accurate spatial and temporal predictions of disease activity, as it occurred first in southern Somalia and then through much of Kenya before affecting northern Tanzania, provided a 2 to 6 week period of warning for the Horn of Africa that facilitated disease outbreak response and mitigation activities. This is the first prospective prediction of a Rift Valley fever outbreak

Global Disease Outbreaks Associated with the 2015–2016 El Niño Event

Interannual climate variability patterns associated with the El Niño-Southern Oscillation phenomenon result in climate and environmental anomaly conditions in specific regions worldwide that directly favor outbreaks and/or amplification of variety of diseases of public health concern including chikungunya, hantavirus, Rift Valley fever, cholera, plague, and Zika. We analyzed patterns of some disease outbreaks during the strong 2015–2016 El Niño event in relation to climate anomalies derived from satellite measurements. Disease outbreaks in multiple El Niño-connected regions worldwide (including Southeast Asia, Tanzania, western US, and Brazil) followed shifts in rainfall, temperature, and vegetation in which both drought and flooding occurred in excess (14–81% precipitation departures from normal). These shifts favored ecological conditions appropriate for pathogens and their vectors to emerge and propagate clusters of diseases activity in these regions. Our analysis indicates that intensity of disease activity in some ENSO-teleconnected regions were approximately 2.5–28% higher during years with El Niño events than those without. Plague in Colorado and New Mexico as well as cholera in Tanzania were significantly associated with above normal rainfall (p \u3c 0.05); while dengue in Brazil and southeast Asia were significantly associated with above normal land surface temperature (p \u3c 0.05). Routine and ongoing global satellite monitoring of key climate variable anomalies calibrated to specific regions could identify regions at risk for emergence and propagation of disease vectors. Such information can provide sufficient lead-time for outbreak prevention and potentially reduce the burden and spread of ecologically coupled diseases

Establishing a malaria diagnostics centre of excellence in Kisumu, Kenya

<p>Abstract</p> <p>Background</p> <p>Malaria microscopy, while the gold standard for malaria diagnosis, has limitations. Efficacy estimates in drug and vaccine malaria trials are very sensitive to small errors in microscopy endpoints. This fact led to the establishment of a Malaria Diagnostics Centre of Excellence in Kisumu, Kenya. The primary objective was to ensure valid clinical trial and diagnostic test evaluations. Key secondary objectives were technology transfer to host countries, establishment of partnerships, and training of clinical microscopists.</p> <p>Case description</p> <p>A twelve-day "long" and a four-day "short" training course consisting of supervised laboratory practicals, lectures, group discussions, demonstrations, and take home assignments were developed. Well characterized slides were developed and training materials iteratively improved. Objective pre- and post-course evaluations consisted of 30 slides (19 negative, 11 positive) with a density range of 50–660 parasites/μl, a written examination (65 questions), a photographic image examination (30 images of artifacts and species specific characteristics), and a parasite counting examination.</p> <p>Discussion and Evaluation</p> <p>To date, 209 microscopists have participated from 11 countries. Seventy-seven experienced microscopists participated in the "long" courses, including 47 research microscopists. Sensitivity improved by a mean of 14% (CI 9–19%) from 77% baseline (CI 73–81 %), while specificity improved by a mean of 17% (CI 11–23%) from 76% (CI 70–82%) baseline. Twenty-three microscopists who had been selected for a four-day refresher course showed continued improvement with a mean final sensitivity of 95% (CI 91–98%) and specificity of 97% (CI 95–100%). Only 9% of those taking the pre-test in the "long" course achieved a 90% sensitivity and 95% specificity, which increased to 61% of those completing the "short" course. All measures of performance improved substantially across each of the five organization types and in each course offered.</p> <p>Conclusion</p> <p>The data clearly illustrated that false positive and negative malaria smears are a serious problem, even with research microscopists. Training dramatically improved performance. Quality microscopy can be provided by the Centre of Excellence concept. This concept can be extended to other diagnostics of public health importance, and comprehensive disease control strategies.</p

Using outbreak science to strengthen the use of models during epidemics.

Infectious disease modeling has played a prominent role in recent outbreaks, yet integrating these analyses into public health decision-making has been challenging. We recommend establishing ‘outbreak science’ as an inter-disciplinary field to improve applied epidemic modeling