| Literature DB >> 21388569 |
Mark M Fukuda1, Terry A Klein, Tadeusz Kochel, Talia M Quandelacy, Bryan L Smith, Jeff Villinski, Delia Bethell, Stuart Tyner, Youry Se, Chanthap Lon, David Saunders, Jacob Johnson, Eric Wagar, Douglas Walsh, Matthew Kasper, Jose L Sanchez, Clara J Witt, Qin Cheng, Norman Waters, Sanjaya K Shrestha, Julie A Pavlin, Andres G Lescano, Paul C F Graf, Jason H Richardson, Salomon Durand, William O Rogers, David L Blazes, Kevin L Russell, Hoseah Akala, Joel C Gaydos, Robert F DeFraites, Panita Gosi, Ans Timmermans, Chad Yasuda, Gary Brice, Fred Eyase, Karl Kronmann, Peter Sebeny, Robert Gibbons, Richard Jarman, John Waitumbi, David Schnabel, Allen Richards, Dennis Shanks.
Abstract
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.Entities:
Mesh:
Year: 2011 PMID: 21388569 PMCID: PMC3092419 DOI: 10.1186/1471-2458-11-S2-S9
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 3.295
Figure 1Map inset: Major Accomplishments of the AFHSC-GEIS Vector-borne Illness Surveillance Program
Concepts for the AFHSC-GEIS Vector-Borne Infection (VBI) Surveillance Program
| Concept | Rationale |
|---|---|
| Programmatic organization of surveillance efforts as VBIs is a useful principle to prioritize surveillance efforts | Strict adherence to a VBI-only surveillance program must be balanced with an understanding of prevailing disease threats |
| VBI surveillance efforts should be closely coordinated with human surveillance | Although disease burden in zoonotic or vector populations is of interest, it is so primarily because of the potential impact on humans |
| Human VBI case definitions should require laboratory confirmation | Clinical diagnoses of most VBI are of limited sensitivity and specificity; pathogen level identification will guide effective treatment |
| Case definitions employed should be able to be applied consistently across disparate geographies and longitudinally | If surveillance goal is to map disease in areas of sparse infrastructure, simpler laboratory techniques may be preferable |
| Advancing technologies should be evaluated continually and incorporated without jeopardizing capability for analysis of longitudinal trend | Balance must be achieved between newer diagnostic technologies and adherence to established laboratory case definitions. Substitution of more sensitive methods may erroneously mimic disease emergence |
| Standardized laboratory and clinical approaches should be judiciously applied and implemented based on proximal impact on human health | The imperative for a “standardized” surveillance system must be tempered with consideration for the cost-benefit ratio of implementing such standards |
| To properly power epidemiological studies over a broad geography, laboratory case definitions may diverge from those typically used to guide clinical diagnoses | Example: Studies intended to define the geospatial extent of antimicrobial drug resistance might seek to characterize genotypes from extracted DNA rather than rely on determination of minimum inhibitory concentrations (MICs) from viable organisms, despite the fact that the latter may be more predictive of clinical outcome |
| Patient samples and associated clinical data must be recorded and maintained in a data and specimen repository in a consistent manner over time | Longitudinal trends can be better assessed if specimens and associated demographic data are catalogued in a manner to allow for retrospective trend analysis |
| Full use must be made of existing, appropriately collected and catalogued sample sets for retroactive analysis | As technology advances, capability to diagnose previously “undiscovered” pathogens can be applied retroactively to banked specimens to better determine the pace of emergence |
Military Infectious Disease Impact Rank: Top 20 febrile illnesses ranked by order of military significance.
| Rank | Disease | Median GRSI Score | Medical Force ICDT Rank | Military Impact Index (GRSI/ICDT Rank) |
|---|---|---|---|---|
| 1 | Malaria | 4949 | 1 | 4949 |
| 2 | Diarrhea, bacterial | 5236 | 3 | 1745 |
| 3 | Dengue | 3148 | 2 | 1574 |
| 4 | Norovirus and other viral diarrhea | 1964* | 7 | 280 |
| 5 | Leptospirosis | 1745 | 10 | 174 |
| 6 | Chikungunya | 2608 | 16 | 163 |
| 7 | Rift Valley Fever | 2519 | 24 | 104 |
| 8 | HIV/AIDS | 728 | 14 | 52 |
| 9 | Meningococcal meningitis | 698 | 17 | 41 |
| 10 | Diarrhea, protozoal | 411 | 11 | 37 |
| 11 | Crimean-Congo hemorrhagic fever | 430 | 13 | 33 |
| 12 | Leishmaniasis | 12 | 5 | 24 |
| 13 | Hepatitis E | 402 | 21 | 19 |
| 14 | Hemorrhagic fever with renal syndrome | 252 | 15 | 16 |
| 15 | Q fever ( | 92 | 6 | 15 |
| 16 | Rickettsioses | 155 | 19 | 8 |
| 17 | Tick Borne encephalitis | 134 | 23 | 5 |
| 18 | Influenza | 35 | 8 | 4 |
| 19 | Plague | 89 | 18 | 4 |
| 20 | Lassa/other arenaviruses | 63 | 22 | 2 |
Index calculated as quotient of Infectious Diseases Investment Decision Evaluation Algorithm (ID-IDEAL) Global Risk Severity Index (GRSI)/Integrated Capabilities Development Team (ICDT) rank for diseases listed in both documents. Adapted from refs 27 and 28.
*Mean of all GSRI scores for diarrheal diseases
+Mean of cutaneous, visceral and mucosal leishmaniasis GSRI scores