Vector borne diseases like Japanese Encephalitis (JE) result from the convergence of multiple factors, including, but not limited to, human, animal, environmental, and economic and social determinants. Thus, to combat these problems, it is essential to have a systematic understanding of drivers and determinants based on a surveillance system that systematically gathers and analyzes data emanating from across multiple disciplines.
Mosquito
During 2011, dengue fever emerged as a serious public health problem in Punjab, Pakistan. This crisis highlighted gaping holes in the health system. It was realized that the present system is unlikely to have the capacity in responding to an emergency of this magnitude. Since 1994, the cases of dengue fever are being frequently reported in different regions of Pakistan. However, this deadly attack of dengue virus exposed the government’s weaknesses in handling emergencies.
Dengue hemorraghic fever (DHF) is affecting more than 50 million people globally and still remains a persistent public health challenge in Saudi Arabia [1]. Althougth there has been available financial resource, limitations and deficiencies in integrated DHF control management strategy implementation and surveillance capacity have hindered the effective implementation of recommended WHO and Global One Health (OH) strategic guidelines and measures in DHF control and elimination in remotes urban and rural settings in Saudi Arabia[1, 2].
Large mosquito outbreaks mysteriously began to recur annually in Western Kentucky beginning in 2011. With up to 30 bites/minute in urban areas, these outbreaks warranted Governor-declared public health emergencies requiring expensive ($2 million each) aerial insecticide applications over 300,000 – 700,000 acres of populated area. The economic impact was also significant because the area, with large reservoirs managed by the TVA, is one of Kentucky’s most important tourist destinations.
Description
DENV, CHIKV and ZIKV are all transmitted by mosquitoes and have occurred in outbreaks in the Caribbean. Common symptoms (which can be severe and disabling) are similar among the 3 viruses and include fever, joint pain/swelling, headache, muscle pain and rash. In December 2015, the first endemic case of ZIKV infection was reported by VACHS. Since that time, an increasing number of ZIKV infections have been reported in Puerto Rico. Due to the growing ZIKV outbreak, we performed ongoing testing and surveillance.
Objective
We describe surveillance for Dengue virus (DENV), Chikungunya virus (CHIKV) and Zika virus (ZIKV) in VA Caribbean Healthcare System (VACHS) from the start of ZIKV transmission in Puerto Rico.
Description
Since 2003 some Arizona counties have followed mosquito surveillance protocols to trap the West Nile Virus vector, Culex spp., using CO2 traps. Despite low sensitivity of these traps to detect Aedes spp., one out of seven CO2 traps deployed in Santa Cruz County detected Aedes aegypti in 2014. Enhancing surveillance for Aedes spp. in this region is critical, given that local transmission of dengue has occured across the border in Nogales, Sonora. Limited resources in Santa Cruz County have previously inhibited efforts to enhance mosquito surveillance . To broaden the reach of county surveillance, we implemented a community participatory project by engaging residents to conduct ovitrapping, a non-technical trap that attracts Aedes spp.
Objective
The objective of this work is to develop an efficient communitybased strategy to enhance mosquito surveillance for Aedes spp., vector for chikungunya and dengue viruses, in Santa Cruz County on the U.S.-Mexico border. We aim to determine vector presence, distribution, and seasonality by using ovitraps maintained by community members.
Description
Neill’s fast subset scan2 detects significant spatial patterns of disease by efficiently maximizing a log-likelihood ratio statistic over subsets of locations, but may result in patterns that are not spatially compact. The penalized fast subset scan (PFSS)3 provides a flexible framework for adding soft constraints to the fast subset scan, rewarding or penalizing inclusion of individual points into a cluster with additive point-specific penalty terms. We propose the support vector subset scan (SVSS), a novel method that iteratively assigns penalties according to distance from the separating hyperplane learned by a kernel support vector machine (SVM). SVSS efficiently detects disease clusters that are geometrically compact and irregular.
Objective
We present the support vector subset scan (SVSS), a new method for detecting localized and irregularly shaped patterns in spatial data. SVSS integrates the penalized fast subset scan3 with a kernel support vector machine classifier to accurately detect disease clusters that are compact and irregular in shape.
Description
As part of a statewide effort to enhance surveillance for Aedes spp.mosquitoes the Office of Border Health (OBH) took the lead inproviding technical assistance on surveillance in counties bordering Mexico. In 2016, OBH sought ways to enhance surveillance in a wider geographic area. Trap locations closer to the border were established as a priority, given high amount of traffic across the international line, high border Aedesmosquito activity, and native cases of dengue reported at the border in Mexico.
Objective
This surveillance project aims to increase and broaden coverage o fAedes spp. ovitrap locations in Arizona’s U.S.- Mexico border region through interagency collaboration.
Description
There were several stand-alone vector surveillance applications being used by the New York State Department of Health (NYSDOH) to support the reporting of mosquito, bird, and mammal surveillance and infection information implemented in early 2000s in response to West Nile virus. In subsequent years, the Electronic Clinical Laboratory Reporting System (ECLRS) and the Communicable Disease Electronic Surveillance System (CDESS) were developed and integrated to be used for surveillance and investigations of human infectious diseases and management of outbreaks.
An integrated vector surveillance system project was proposed to address the migration of the stand-alone vector surveillance applications into a streamlined, consolidated solution to support operational, management, and technical needs by using the national standards with the existing resources and technical environment.
Objective
To develop a mosquito surveillance module to collect mosquito information testing for West Nile, East Equine Encephalitis (EEE) and Zika viruses using national standards. To provide a common set of data for local health departments (LHDs) and state users to report and share information. To monitor the type of mosquito species that carry diseases.