The AFHSC-Division of GEIS Operations Predictive Surveillance Program: a multidisciplinary approach for the early detection and response to disease outbreaks

Intimate Partner Violence-Related Brain Injury: Unmasking and Addressing the Gaps

Intimate partner violence (IPV) is a significant, global public health concern. Women, individuals with historically underrepresented identities, and disabilities are at high risk for IPV and tend to experience severe injuries. There has been growing concern about the risk of exposure to IPV-related head trauma, resulting in IPV-related brain injury (IPV-BI), and its health consequences. Past work suggests that a significant proportion of women exposed to IPV experience IPV-BI, likely representing a distinct phenotype compared with BI of other etiologies. An IPV-BI often co-occurs with psychological trauma and mental health complaints, leading to unique issues related to identifying, prognosticating, and managing IPV-BI outcomes. The goal of this review is to identify important gaps in research and clinical practice in IPV-BI and suggest potential solutions to address them. We summarize IPV research in five key priority areas: (1) unique considerations for IPV-BI study design; (2) understanding non-fatal strangulation as a form of BI; (3) identifying objective biomarkers of IPV-BI; (4) consideration of the chronicity, cumulative and late effects of IPV-BI; and (5) BI as a risk factor for IPV engagement. Our review concludes with a call to action to help investigators develop ecologically valid research studies addressing the identified clinical-research knowledge gaps and strategies to improve care in individuals exposed to IPV-BI. By reducing the current gaps and answering these calls to action, we will approach IPV-BI in a trauma-informed manner, ultimately improving outcomes and quality of life for those impacted by IPV-BI.

Distinguishing Abrupt and Gradual Forest Disturbances With MODIS-Based Phenological Anomaly Series

Capturing forest disturbances over time is increasingly important to determine the ecosystem's capacity to recover as well as aiding a timely response of foresters. With changes due to climate change increasing the frequencies, a better understanding of forest disturbances and their role in historical development is needed to, on the one hand, develop forest management approaches promoting ecosystem resilience and, on the other hand, provide quick and spatially explicit information to foresters. A large, publicly available satellite imagery spanning more than two decades for large areas of the Earth's surface at varying spatial and temporal resolutions represents a vast, free data source for this. The challenge is 2-fold: (1) obtaining reliable information on forest condition and development from satellite data requires not only quantification of forest loss but rather a differentiated assessment of the extent and severity of forest degradation; (2) standardized and efficient processing routines both are needed to bridge the gap between remote-sensing signals and conventional forest condition parameters to enable forest managers for the operational use of the data. Here, we investigated abiotic and biotic disturbances based on a set of ground validated occurrences in various forest areas across Germany to build disturbance response chronologies and examine event-specific patterns. The proposed workflow is based on the R-package "npphen" for non-parametric vegetation phenology reconstruction and anomaly detection using MODIS EVI time series data. Results show the potential to detect distinct disturbance responses in forest ecosystems and reveal event-specific characteristics. Difficulties still exist for the determination of, e.g., scattered wind throw, due to its subpixel resolution, especially in highly fragmented landscapes and small forest patches. However, the demonstrated method shows potential for operational use as a semi-automatic system to augment terrestrial monitoring in the forestry sector. Combining the more robust EVI and the assessment of the phenological series at a pixel-by-pixel level allows for a changing species cover without false classification as forest loss.

Global implications of biodiversity loss on pandemic disease: COVID-19

Unpredictable climate changes and adverse effects on the planetary health due to environmental degradation have led to the rise of concerns regarding human wellness in the recent days. Coronavirus disease 2019 (COVID-19) is said to be originated from wildlife species and represents a significant threat to human health, social, food, and economic security. However, understanding the underlying factors behind the emergence is still rudimentary. This study has made efforts to understand the relationship between the drivers that causes the emergence of infectious diseases (EID). The recent biodiversity crisis that has a severe impact on planetary health is a new contributory factor for the emergence of COVID-19. The biodiversity crisis is an outcome of the land use and land cover (LULC) change, contributing to climate change. In the overall global LULC, 60% are associated with direct human activities and 40% indirect causes such as climate change. Climate change is one of the critical factors that induce landcover change, associated with increasing consumerism, environmental pollution, excessive livestock production, population explosion, and food production. Geospatial techniques provide a viable solution for monitoring the key drivers responsible for EID, such as climate characteristics, LULC, global land cover under food production, and locations affected by infectious diseases in the past. The study’s main objective is to discuss the possibilities of evolving novel solutions to approach the forecasting of emerging infectious disease spread and its mitigation, bridging the sectors and stakeholders, with due relevance to sustainable development goals (SDGs) and other dimensions from global to community levels.

Scoping future outbreaks: a scoping review on the outbreak prediction of the WHO Blueprint list of priority diseases

BACKGROUND

The WHO's Research and Development Blueprint priority list designates emerging diseases with the potential to generate public health emergencies for which insufficient preventive solutions exist. The list aims to reduce the time to the availability of resources that can avert public health crises. The current SARS-CoV-2 pandemic illustrates that an effective method of mitigating such crises is the pre-emptive prediction of outbreaks. This scoping review thus aimed to map and identify the evidence available to predict future outbreaks of the Blueprint diseases.

METHODS

We conducted a scoping review of PubMed, Embase and Web of Science related to the evidence predicting future outbreaks of Ebola and Marburg virus, Zika virus, Lassa fever, Nipah and Henipaviral disease, Rift Valley fever, Crimean-Congo haemorrhagic fever, Severe acute respiratory syndrome, Middle East respiratory syndrome and Disease X. Prediction methods, outbreak features predicted and implementation of predictions were evaluated. We conducted a narrative and quantitative evidence synthesis to highlight prediction methods that could be further investigated for the prevention of Blueprint diseases and COVID-19 outbreaks.

RESULTS

Out of 3959 articles identified, we included 58 articles based on inclusion criteria. 5 major prediction methods emerged; the most frequent being spatio-temporal risk maps predicting outbreak risk periods and locations through vector and climate data. Stochastic models were predominant. Rift Valley fever was the most predicted disease. Diseases with complex sociocultural factors such as Ebola were often predicted through multifactorial risk-based estimations. 10% of models were implemented by health authorities. No article predicted Disease X outbreaks.

CONCLUSIONS

Spatiotemporal models for diseases with strong climatic and vectorial components, as in River Valley fever prediction, may currently best reduce the time to the availability of resources. A wide literature gap exists in the prediction of zoonoses with complex sociocultural and ecological dynamics such as Ebola, COVID-19 and especially Disease X.

International Rickettsia Disease Surveillance: An Example of Cooperative Research to Increase Laboratory Capability and Capacity for Risk Assessment of Rickettsial Outbreaks Worldwide

Cooperative research that addresses infectious disease surveillance and outbreak investigations relies heavily on availability and effective use of appropriate diagnostic tools, including serological and molecular assays, as exemplified by the current COVID-19 pandemic. In this paper, we stress the importance of using these assays to support collaborative epidemiological studies to assess risk of rickettsial disease outbreaks among international partner countries. Workforce development, mentorship, and training are important components in building laboratory capability and capacity to assess risk of and mitigate emerging disease outbreaks. International partnerships that fund cooperative research through mentoring and on-the-job training are successful examples for enhancing infectious disease surveillance. Cooperative research studies between the Naval Medical Research Center's Rickettsial Diseases Research Program (RDRP) and 17 institutes from nine countries among five continents were conducted to address the presence of and the risk for endemic rickettsial diseases. To establish serological and molecular assays in the collaborative institutes, initial training and continued material, and technical support were provided by RDRP. The laboratory methods used in the research studies to detect and identify the rickettsial infections included (1) group-specific IgM and IgG serological assays and (2) molecular assays. Twenty-six cooperative research projects performed between 2008 and 2020 enhanced the capability and capacity of 17 research institutes to estimate risk of rickettsial diseases. These international collaborative studies have led to the recognition and/or confirmation of rickettsial diseases within each of the partner countries. In addition, with the identification of specific pathogen and non-pathogen Rickettsia species, a more accurate risk assessment could be made in surveillance studies using environmental samples. The discoveries from these projects reinforced international cooperation benefiting not only the partner countries but also the scientific community at large through presentations (n = 40) at international scientific meetings and peer-reviewed publications (n = 18). The cooperative research studies conducted in multiple international institutes led to the incorporation of new SOPs and trainings for laboratory procedures; biosafety, biosurety, and biosecurity methods; performance of rickettsia-specific assays; and the identification of known and unknown rickettsial agents through the introduction of new serologic and molecular assays that complemented traditional microbiology methods.

Data and tools to integrate climate and environmental information into public health

BACKGROUND

During the last 30 years, the development of geographical information systems and satellites for Earth observation has made important progress in the monitoring of the weather, climate, environmental and anthropogenic factors that influence the reduction or the reemergence of vector-borne diseases. Analyses resulting from the combination of geographical information systems (GIS) and remote sensing have improved knowledge of climatic, environmental, and biodiversity factors influencing vector-borne diseases (VBDs) such as malaria, visceral leishmaniasis, dengue, Rift Valley fever, schistosomiasis, Chagas disease and leptospirosis. These knowledge and products developed using remotely sensed data helped and continue to help decision makers to better allocate limited resources in the fight against VBDs.

MAIN BODY

Because VBDs are linked to climate and environment, we present here our experience during the last four years working with the projects under the, World Health Organization (WHO)/ The Special Programme for Research and Training in Tropical Diseases (TDR)-International Development Research Centre (IDRC) Research Initiative on VBDs and Climate Change to integrate climate and environmental information into research and decision-making processes. The following sections present the methodology we have developed, which uses remote sensing to monitor climate variability, environmental conditions, and their impacts on the dynamics of infectious diseases. We then show how remotely sensed data can be accessed and evaluated and how they can be integrated into research and decision-making processes for mapping risks, and creating Early Warning Systems, using two examples from the WHO TDR projects based on schistosomiasis analysis in South Africa and Trypanosomiasis in Tanzania.

CONCLUSIONS

The tools presented in this article have been successfully used by the projects under the WHO/TDR-IDRC Research Initiative on VBDs and Climate Change. Combined with capacity building, they are an important piece of work which can significantly contribute to the goals of WHO Global Vector Control Response and to the Sustainable Development Goals especially those on health and climate action.

Translating Predictions of Zoonotic Viruses for Policymakers

Recent outbreaks of Ebola virus disease and Zika virus disease highlight the need for disseminating accurate predictions of emerging zoonotic viruses to national governments for disease surveillance and response. Although there are published maps for many emerging zoonotic viruses, it is unknown if there is agreement among different models or if they are concordant with national expert opinion. Therefore, we reviewed existing predictions for five high priority emerging zoonotic viruses with national experts in Cameroon to investigate these issues and determine how to make predictions more useful for national policymakers. Predictive maps relied primarily on environmental parameters and species distribution models. Rift Valley fever virus and Crimean-Congo hemorrhagic fever virus predictions differed from national expert opinion, potentially because of local livestock movements. Our findings reveal that involving national experts could elicit additional data to improve predictions of emerging pathogens as well as help repackage predictions for policymakers.

Wetlands, wild Bovidae species richness and sheep density delineate risk of Rift Valley fever outbreaks in the African continent and Arabian Peninsula

Rift Valley fever (RVF) is an emerging, vector-borne viral zoonosis that has significantly impacted public health, livestock health and production, and food security over the last three decades across large regions of the African continent and the Arabian Peninsula. The potential for expansion of RVF outbreaks within and beyond the range of previous occurrence is unknown. Despite many large national and international epidemics, the landscape epidemiology of RVF remains obscure, particularly with respect to the ecological roles of wildlife reservoirs and surface water features. The current investigation modeled RVF risk throughout Africa and the Arabian Peninsula as a function of a suite of biotic and abiotic landscape features using machine learning methods. Intermittent wetland, wild Bovidae species richness and sheep density were associated with increased landscape suitability to RVF outbreaks. These results suggest the role of wildlife hosts and distinct hydrogeographic landscapes in RVF virus circulation and subsequent outbreaks may be underestimated. These results await validation by studies employing a deeper, field-based interrogation of potential wildlife hosts within high risk taxa.

Rift Valley fever (RVF) is a vector-borne zoonotic disease that imparts a substantial burden to the economy and public health of pastoralist communities across the African continent and Arabian Peninsula. Furthermore, RVF is also an emerging pathogen of growing global concern. Knowledge of the epidemiological and ecological factors that influence the geographic distribution of RVF outbreaks and determine risk for humans and animals is incomplete. The current study examined the distribution of RVF outbreaks from 1998 to 2016 and modeled their occurrence as a function of climate, surface water, land cover, livestock density, wild mammalian species richness, and human migration. The results indicate that wetlands, Bovidae species richness, and sheep density were associated with increased risk of RVF outbreaks. Our findings contribute to improved understanding of the spatial and ecological dynamics of RVF risk with a particular emphasis on the distribution of wetlands and potential wildlife reservoirs in designing RVF surveillance programs.

Prioritization of High Consequence Viruses to Improve European Laboratory Preparedness for Cross-Border Health Threats

Highly infectious diseases can spread rapidly across borders through travel or trade, and international coordination is essential to a prompt and efficient response by public health laboratories. Therefore, developing strategies to identify priorities for a rational allocation of resources for research and surveillance has been the focus of a large body of research in recent years. This paper describes the activities and the strategy used by a European-wide consortium funded by the European Commission, named EMERGE (Efficient response to highly dangerous and emerging pathogens at EU level), for the selection of high-threat pathogens with cross-border potential that will become the focus of its preparedness activities. The approach used is based on an objective scoring system, a close collaboration with other networks dealing with highly infection diseases, and a diagnostic gaps analysis. The result is a tool that is simple, objective and adaptable, which will be used periodically to re-evaluate activities and priorities, representing a step forward towards a better response to infectious disease emergencies.

Joint use of Disparate Data for the Surveillance of Zoonoses: A Feasibility Study for a One Health Approach in Germany

Zoonotic diseases concern human and animal populations and are transmitted between both humans and animals. Nevertheless, surveillance data on zoonoses are collected separately for the most part in different databases for either humans or animals. Bearing in mind the concept of One Health, it is assumed that a global view of these data might help to prevent and control zoonotic diseases. In following this approach, we wanted to determine which zoonotic data are routinely collected in Germany and whether these data could be integrated in a useful way to improve surveillance. Therefore, we conducted an inventory of the existing data collections and gathered information on possible One Health surveillance areas in Germany by approaching experts through a scoping survey, personal interviews and during a workshop. In matching the information between the status quo for existing data collections and the possible use cases for One Health surveillance, this study revealed that data integration is currently hindered by missing data, missing pathogen information or a lack of timeliness, depending on the surveillance purpose. Therefore, integrating the existing data would require substantial efforts and changes to adapt the collection procedures for routine databases. Nevertheless, during this study, we observed a need for different stakeholders from the human and animal health sectors to share information to improve the surveillance of zoonoses. Therefore, our findings suggest that before the data sets from different databases are integrated for joint analyses, the surveillance could be improved by the sharing of information and knowledge through a collaboration of stakeholders from different sectors and institutions.

ORBiT: Oak Ridge biosurveillance toolkit for public health dynamics

Background

The digitization of health-related information through electronic health records (EHR) and electronic healthcare reimbursement claims and the continued growth of self-reported health information through social media provides both tremendous opportunities and challenges in developing effective biosurveillance tools. With novel emerging infectious diseases being reported across different parts of the world, there is a need to build systems that can track, monitor and report such events in a timely manner. Further, it is also important to identify susceptible geographic regions and populations where emerging diseases may have a significant impact.

Methods

In this paper, we present an overview of Oak Ridge Biosurveillance Toolkit (ORBiT), which we have developed specifically to address data analytic challenges in the realm of public health surveillance. In particular, ORBiT provides an extensible environment to pull together diverse, large-scale datasets and analyze them to identify spatial and temporal patterns for various biosurveillance-related tasks.

Results

We demonstrate the utility of ORBiT in automatically extracting a small number of spatial and temporal patterns during the 2009-2010 pandemic H1N1 flu season using claims data. These patterns provide quantitative insights into the dynamics of how the pandemic flu spread across different parts of the country. We discovered that the claims data exhibits multi-scale patterns from which we could identify a small number of states in the United States (US) that act as "bridge regions" contributing to one or more specific influenza spread patterns. Similar to previous studies, the patterns show that the south-eastern regions of the US were widely affected by the H1N1 flu pandemic. Several of these south-eastern states act as bridge regions, which connect the north-east and central US in terms of flu occurrences.

Conclusions

These quantitative insights show how the claims data combined with novel analytical techniques can provide important information to decision makers when an epidemic spreads throughout the country. Taken together ORBiT provides a scalable and extensible platform for public health surveillance.

Rift Valley fever virus: A review of diagnosis and vaccination, and implications for emergence in Europe

Rift Valley fever virus (RVFV) is a mosquito-borne virus, and is the causative agent of Rift Valley fever (RVF), a zoonotic disease characterised by an increased incidence of abortion or foetal malformation in ruminants. Infection in humans can also lead to clinical manifestations that in severe cases cause encephalitis or haemorrhagic fever. The virus is endemic throughout much of the African continent. However, the emergence of RVFV in the Middle East, northern Egypt and the Comoros Archipelago has highlighted that the geographical range of RVFV may be increasing, and has led to the concern that an incursion into Europe may occur. At present, there is a limited range of veterinary vaccines available for use in endemic areas, and there is no licensed human vaccine. In this review, the methods available for diagnosis of RVFV infection, the current status of vaccine development and possible implications for RVFV emergence in Europe, are discussed.

Early detection for cases of enterovirus- and influenza-like illness through a newly established school-based syndromic surveillance system in Taipei, January 2010 ~ August 2011

School children may transmit pathogens with cluster cases occurring on campuses and in families. In response to the 2009 influenza A (H1N1) pandemic, Taipei City Government officials developed a School-based Infectious Disease Syndromic Surveillance System (SID-SSS). Teachers and nurses from preschools to universities in all 12 districts within Taipei are required to daily report cases of symptomatic children or sick leave requests through the SID-SSS. The pre-diagnosis at schools is submitted firstly as common pediatric disease syndrome-groups and re-submitted after confirmation by physicians. We retrieved these data from January 2010 to August 2011 for spatio-temporal analysis and evaluated the temporal trends with cases obtained from both the Emergency Department-based Syndromic Surveillance System (ED-SSS) and the Longitudinal Health Insurance Database 2005 (LHID2005). Through the SID-SSS, enterovirus-like illness (EVI) and influenza-like illness (ILI) were the two most reported syndrome groups (77.6% and 15.8% among a total of 19,334 cases, respectively). The pre-diagnosis judgments made by school teachers and nurses showed high consistency with physicians' clinical diagnoses for EVI (97.8%) and ILI (98.9%). Most importantly, the SID-SSS had better timeliness with earlier peaks of EVI and ILI than those in the ED-SSS. Furthermore, both of the syndrome groups in these two surveillance systems had the best correlation reaching 0.98 and 0.95, respectively (p<0.01). Spatio-temporal analysis observed the patterns of EVI and ILI both diffuse from the northern suburban districts to central Taipei, with ILI spreading faster. This novel system can identify early suspected cases of two important pediatric infections occurring at schools, and clusters from schools/families. It was also cost-effective (95.5% of the operation cost reduced and 59.7% processing time saved). The timely surveillance of mild EVI and ILI cases integrated with spatial analysis may help public health decision-makers with where to target for enhancing surveillance and prevention measures to minimize severe cases.

Global climate anomalies and potential infectious disease risks: 2014-2015

Background: The El Niño/Southern Oscillation (ENSO) is a global climate phenomenon that impacts human infectious disease risk worldwide through droughts, floods, and other climate extremes. Throughout summer and fall 2014 and winter 2015, El Niño Watch, issued by the US National Oceanic and Atmospheric Administration, assessed likely El Niño development during the Northern Hemisphere fall and winter, persisting into spring 2015. Methods: We identified geographic regions where environmental conditions may increase infectious disease transmission if the predicted El Niño occurs using El Niño indicators (Sea Surface Temperature [SST], Outgoing Longwave Radiation [OLR], and rainfall anomalies) and literature review of El Niño-infectious disease associations. Results: SSTs in the equatorial Pacific and western Indian Oceans were anomalously elevated during August-October 2014, consistent with a developing weak El Niño event. Teleconnections with local climate is evident in global precipitation patterns, with positive OLR anomalies (drier than average conditions) across Indonesia and coastal southeast Asia, and negative anomalies across northern China, the western Indian Ocean, central Asia, north-central and northeast Africa, Mexico/Central America, the southwestern United States, and the northeastern and southwestern tropical Pacific. Persistence of these conditions could produce environmental settings conducive to increased transmission of cholera, dengue, malaria, Rift Valley fever, and other infectious diseases in regional hotspots as during previous El Niño events. Discussion and Conclusions: The current development of weak El Niño conditions may have significant potential implications for global public health in winter 2014-spring 2015. Enhanced surveillance and other preparedness measures in predicted infectious disease hotspots could mitigate health impacts.

Simulation modelling of population dynamics of mosquito vectors for rift valley Fever virus in a disease epidemic setting

BACKGROUND

Rift Valley Fever (RVF) is weather dependent arboviral infection of livestock and humans. Population dynamics of mosquito vectors is associated with disease epidemics. In our study, we use daily temperature and rainfall as model inputs to simulate dynamics of mosquito vectors population in relation to disease epidemics.

METHODS/FINDINGS

Time-varying distributed delays (TVDD) and multi-way functional response equations were implemented to simulate mosquito vectors and hosts developmental stages and to establish interactions between stages and phases of mosquito vectors in relation to vertebrate hosts for infection introduction in compartmental phases. An open-source modelling platforms, Universal Simulator and Qt integrated development environment were used to develop models in C++ programming language. Developed models include source codes for mosquito fecundity, host fecundity, water level, mosquito infection, host infection, interactions, and egg time. Extensible Markup Language (XML) files were used as recipes to integrate source codes in Qt creator with Universal Simulator plug-in. We observed that Floodwater Aedines and Culicine population continued to fluctuate with temperature and water level over simulation period while controlled by availability of host for blood feeding. Infection in the system was introduced by floodwater Aedines. Culicines pick infection from infected host once to amplify disease epidemic. Simulated mosquito population show sudden unusual increase between December 1997 and January 1998 a similar period when RVF outbreak occurred in Ngorongoro district.

CONCLUSION/SIGNIFICANCE

Findings presented here provide new opportunities for weather-driven RVF epidemic simulation modelling. This is an ideal approach for understanding disease transmission dynamics towards epidemics prediction, prevention and control. This approach can be used as an alternative source for generation of calibrated RVF epidemics data in different settings.

Zoonotic disease surveillance--inventory of systems integrating human and animal disease information

Although 65% of recent major disease outbreaks throughout the world have a zoonotic origin, there is still a sharp division among the disciplines into the human and animal health sectors. In the last few decades, a global integrative concept, often referred to as 'One Health', has been strongly endorsed. Surveillance and monitoring efforts are major components for effective disease prevention and control. As human health and animal health are inextricably linked, it is assumed that a cross-sectoral data interpretation of zoonotic disease information will improve their prevention, prediction and control. To provide an overview of existing systems throughout the world which integrate information from humans and animals on zoonotic diseases, a literature review was conducted. Twenty projects were identified and described regarding their concepts and realization. They all vary widely depending on their surveillance purpose, their structure and the source of information they use. What they have in common is that they quite often use data which have already been collected for another purpose. Therefore, the challenges of how to make use of such secondary data are of great interest.

Environmental changes impacting Echinococcus transmission: research to support predictive surveillance and control

Echinococcosis, resulting from infection with tapeworms Echinococcus granulosus and E. multilocularis, has a global distribution with 2-3 million people affected and 200,000 new cases diagnosed annually. Costs of treatment for humans and economic losses to the livestock industry have been estimated to exceed $2 billion. These figures are likely to be an underestimation given the challenges with its early detection and the lack of mandatory official reporting policies in most countries. Despite this global burden, echinococcosis remains a neglected zoonosis. The importance of environmental factors in influencing the transmission intensity and distribution of Echinococcus spp. is increasingly being recognized. With the advent of climate change and the influence of global population expansion, food insecurity and land-use changes, questions about the potential impact of changing temperature, rainfall patterns, increasing urbanization, deforestation, grassland degradation and overgrazing on zoonotic disease transmission are being raised. This study is the first to comprehensively review how climate change and anthropogenic environmental factors contribute to the transmission of echinococcosis mediated by changes in animal population dynamics, spatial overlap of competent hosts and the creation of improved conditions for egg survival. We advocate rigorous scientific research to establish the causal link between specific environmental variables and echinococcosis in humans and the incorporation of environmental, animal and human data collection within a sentinel site surveillance network that will complement satellite remote-sensing information. Identifying the environmental determinants of transmission risk to humans will be vital for the design of more accurate predictive models to guide cost-effective pre-emptive public health action against echinococcosis.

Influenza serological studies to inform public health action: best practices to optimise timing, quality and reporting

BACKGROUND

Serological studies can detect infection with a novel influenza virus in the absence of symptoms or positive virology, providing useful information on infection that goes beyond the estimates from epidemiological, clinical and virological data. During the 2009 A(H1N1) pandemic, an impressive number of detailed serological studies were performed, yet the majority of serological data were available only after the first wave of infection. This limited the ability to estimate the transmissibility and severity of this novel infection, and the variability in methodology and reporting limited the ability to compare and combine the serological data.

OBJECTIVES

  To identify best practices for conduct and standardisation of serological studies on outbreak and pandemic influenza to inform public policy.

METHODS/SETTING

An international meeting was held in February 2011 in Ottawa, Canada, to foster the consensus for greater standardisation of influenza serological studies.

RESULTS

Best practices for serological investigations of influenza epidemiology include the following: classification of studies as pre-pandemic, outbreak, pandemic or inter-pandemic with a clearly identified objective; use of international serum standards for laboratory assays; cohort and cross-sectional study designs with common standards for data collection; use of serum banks to improve sampling capacity; and potential for linkage of serological, clinical and epidemiological data. Advance planning for outbreak studies would enable a rapid and coordinated response; inclusion of serological studies in pandemic plans should be considered.

CONCLUSIONS

Optimising the quality, comparability and combinability of influenza serological studies will provide important data upon emergence of a novel or variant influenza virus to inform public health action.

Vaccines for canine leishmaniasis

Leishmaniasis is the third most important vector-borne disease worldwide. Visceral leishmaniasis (VL) is a severe and frequently lethal protozoan disease of increasing incidence and severity due to infected human and dog migration, new geographical distribution of the insect due to global warming, coinfection with immunosuppressive diseases, and poverty. The disease is an anthroponosis in India and Central Africa and a canid zoonosis (ZVL) in the Americas, the Middle East, Central Asia, China, and the Mediterranean. The ZVL epidemic has been controlled by one or more measures including the culling of infected dogs, treatment of human cases, and insecticidal treatment of homes and dogs. However, the use of vaccines is considered the most cost-effective control tool for human and canine disease. Since the severity of the disease is related to the generation of T-cell immunosuppression, effective vaccines should be capable of sustaining or enhancing the T-cell immunity. In this review we summarize the clinical and parasitological characteristics of ZVL with special focus on the cellular and humoral canine immune response and review state-of-the-art vaccine development against human and canine VL. Experimental vaccination against leishmaniasis has evolved from the practice of leishmanization with living parasites to vaccination with crude lysates, native parasite extracts to recombinant and DNA vaccination. Although more than 30 defined vaccines have been studied in laboratory models no human formulation has been licensed so far; however three second-generation canine vaccines have already been registered. As expected for a zoonotic disease, the recent preventive vaccination of dogs in Brazil has led to a reduction in the incidence of canine and human disease. The recent identification of several Leishmania proteins with T-cell epitopes anticipates development of a multiprotein vaccine that will be capable of protecting both humans and dogs against VL.

One Health: the global challenge of epidemic and endemic leishmaniasis

'One Health' proposes the unification of medical and veterinary sciences with the establishment of collaborative ventures in clinical care, surveillance and control of cross-species disease, education, and research into disease pathogenesis, diagnosis, therapy and vaccination. The concept encompasses the human population, domestic animals and wildlife, and the impact that environmental changes ('environmental health') such as global warming will have on these populations. Visceral leishmaniasis is a perfect example of a small companion animal disease for which prevention and control might abolish or decrease the suffering of canine and human patients, and which aligns well with the One Health approach. In this review we discuss how surveillance for leishmaniases is undertaken globally through the control of anthroponootic visceral leishmaniasis (AVL) and zoonotic visceral leishmaniasis (ZVL). The ZVL epidemic has been managed to date by the culling of infected dogs, treatment of human cases and control of the sandfly vector by insecticidal treatment of human homes and the canine reservoir. Recently, preventive vaccination of dogs in Brazil has led to reduction in the incidence of the canine and human disease. Vaccination permits greater dog owner compliance with control measures than a culling programme. Another advance in disease control in Africa is provided by a surveillance programme that combines remote satellite sensing, ecological modelling, vector surveillance and geo-spatial mapping of the distribution of vectors and of the animal-to-animal or animal-to-human pathogen transmission. This coordinated programme generates advisory notices and alerts on emerging infectious disease outbreaks that may impede or avoid the spreading of visceral leishmaniasis to new areas of the planet as a consequence of global warming.

Malaria and other vector-borne infection surveillance in the U.S. Department of Defense Armed Forces Health Surveillance Center-Global Emerging Infections Surveillance program: review of 2009 accomplishments

Vector-borne infections (VBI) are defined as infectious diseases transmitted by the bite or mechanical transfer of arthropod vectors. They constitute a significant proportion of the global infectious disease burden. United States (U.S.) Department of Defense (DoD) personnel are especially vulnerable to VBIs due to occupational contact with arthropod vectors, immunological naiveté to previously unencountered pathogens, and limited diagnostic and treatment options available in the austere and unstable environments sometimes associated with military operations. In addition to the risk uniquely encountered by military populations, other factors have driven the worldwide emergence of VBIs. Unprecedented levels of global travel, tourism and trade, and blurred lines of demarcation between zoonotic VBI reservoirs and human populations increase vector exposure. Urban growth in previously undeveloped regions and perturbations in global weather patterns also contribute to the rise of VBIs. The Armed Forces Health Surveillance Center-Global Emerging Infections Surveillance and Response System (AFHSC-GEIS) and its partners at DoD overseas laboratories form a network to better characterize the nature, emergence and growth of VBIs globally. In 2009 the network tested 19,730 specimens from 25 sites for Plasmodium species and malaria drug resistance phenotypes and nearly another 10,000 samples to determine the etiologies of non-Plasmodium species VBIs from regions spanning from Oceania to Africa, South America, and northeast, south and Southeast Asia. This review describes recent VBI-related epidemiological studies conducted by AFHSC-GEIS partner laboratories within the OCONUS DoD laboratory network emphasizing their impact on human populations.