Satellite Hyperspectral Imagery to Support Tick-Borne Infectious Diseases Surveillance.
ABSTRACT: This study proposed the use of satellite hyperspectral imagery to support tick-borne infectious diseases surveillance based on monitoring the variation in amplifier hosts food sources. To verify this strategy, we used the data of the human rickettsiosis occurrences in southeastern Brazil, region in which the emergence of this disease is associated with the rising capybara population. Spatio-temporal analysis based on Monte Carlo simulations was used to identify risk areas of human rickettsiosis and hyperspectral moderate-resolution imagery was used to identify the increment and expansion of sugarcane crops, main food source of capybaras. In general, a pixel abundance associated with increment of sugarcane crops was detected in risk areas of human rickettsiosis. Thus, the hypothesis that there is a spatio-temporal relationship between the occurrence of human rickettsiosis and the sugarcane crops increment was verified. Therefore, due to the difficulty of monitoring locally the distribution of infectious agents, vectors and animal host's, satellite hyperspectral imagery can be used as a complementary tool for the surveillance of tick-borne infectious diseases and potentially of other vector-borne diseases.
Project description:BACKGROUND:Anaplasmosis is an emerging acute febrile disease that is caused by a bite of an Anaplasma phagocytophilum-infected hard tick. As for healthy patients, reports on asymptomatic anaplasmosis resulting from such tick bites are rare. CASE PRESENTATION:A 55-year-old female patient visited the hospital with a tick bite in the right infraclavicular region. The tick was suspected to have been on the patient for more than 10?days. PCR and an indirect immunofluorescence assay (IFA) were performed to identify tick-borne infectious diseases. The blood sample collected at admission yielded a positive result in nested PCR targeting Ehrlichia- or Anaplasma-specific genes groEL and ankA. Subsequent sequencing confirmed the presence of A. phagocytophilum, and seroconversion was confirmed by the IFA involving an A. phagocytophilum antigen slide. PCR detected no Rickettsia-specific genes [outer membrane protein A (ompA) or surface cell antigen 1 (sca1)], but seroconversion of spotted fever group (SFG) rickettsiosis was confirmed by an IFA. CONCLUSIONS:This study genetically and serologically confirmed an asymptomatic A. phagocytophilum infection. Although SFG rickettsiosis was not detected genetically, it was detected serologically. These findings indicate the possibility of an asymptomatic coinfection: anaplasmosis plus SFG rickettsiosis. It is, therefore, crucial for clinicians to be aware of potential asymptomatic anaplasmosis following a tick bite.
Project description:Tick-borne rickettsioses are world-spreading infectious zoonoses. Ticks serve as reservoirs and vectors for Rickettsia and play a key role in transmission of rickettsioses. Most of the Chinese rickettsiosis patients are reported from Northeastern China but the distribution of tick and tick-borne Rickettsia species in Northeastern China remain poorly studied. In this study, a total of 1,286 ticks were captured from the seven counties of Harbin, an area in Northeastern China, and the tick-borne Rickettsia species were identified by PCR and sequencing of rrs, gltA, groEL, ompA and 17-kDa antigen-encoding genes. Of the 5 identified tick species, Haemaphysalis longicornis and Ixodes persulcatus were the predominant tick species in the livestock and vegetation, respectively. Rickettsia raoultii and "Candidatus Rickettsia tarasevichiae" were the two detectable Rickettsia species in the ticks with a 28.8% positive rate but no rickettsiae were found in ticks of Haemaphysalis concinna. R. raoultii detected in 37.6% of the Dermacentor nuttalli, Dermacentor silvarum and H. longicornis ticks while "Ca. R. tarasevichiae" was only present in 22.8% of the I. persulcatus ticks. In particular, the positive rate of both R. raoultii and "Ca. R. tarasevichiae" in ticks from the livestock (40.7%) was significantly higher than that from the vegetation (19.5%). The results indicate that the tick and tick-borne Rickettsia species are diverse in different regions of Harbin due to geographic difference and the ticks from livestock may play a more important role in transmission of rickettsioses to human.
Project description:The association between companion animals and tick-borne rickettsial disease has long been recognized and can be essential to the emergence of rickettsioses. We tested whole blood from dogs in temporary shelters by using PCR for rickettsial infections. Of 93 dogs, 12 (13%) were positive for Rickettsia parkeri, an emerging tick-borne rickettsiosis.
Project description:Rickettsia sibirica sibirica is the causative agent of Siberian or North Asian tick typhus, a tick-borne rickettsiosis known to exist in Siberia and eastern China. Here we present the draft genome of Rickettsia sibirica sibirica strain BJ-90 isolated from Dermacentor sinicus ticks collected in Beijing, China.
Project description:Rickettsia parkeri, a newly recognized tick-borne pathogen of humans in the Americas, is a confirmed cause of spotted fever group rickettsiosis in Argentina. Until recently, almost all cases of R. parkeri rickettsiosis in Argentina have originated from the Paraná River Delta, where entomological surveys have identified populations of R. parkeri-infected Amblyomma triste ticks. In this report, we describe confirmed cases of R. parkeri rickettsiosis from Córdoba and La Rioja provinces, which are located several hundred kilometers inland, and in a more arid ecological region, where A. triste ticks do not occur. Additionally, we identified questing A. tigrinum ticks naturally infected with R. parkeri in Córdoba province. These data provide evidence that another human-biting tick species serves as a potential vector of R. parkeri in Argentina and possibly, other countries of South America.
Project description:Target detection in remote sensing has vital applications in mineral mapping, law enforcement, precision agriculture, strategic surveillance, etc. We present the acquisition of a first-of-its-kind high-resolution multi-platform (ground, airborne, and space-borne) remote sensing-based benchmark dataset for target detection studies. The dataset includes imagery acquired from terrestrial hyperspectral imager (THI), airborne hyperspectral sensor (AVIRIS-NG), and space-borne multi-spectral (Sentinel-2) sensor on 20th March 2018. Five engineered targets of different materials and colours were placed on different surface backgrounds. Besides, in-situ reflectance spectra of the targets were also acquired using a spectroradiometer for serving as a spectral reference source. The airborne and space-borne imagery were processed to remove un-calibrated/noisy bands and were atmospherically corrected using a radiative transfer method based Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) model. The in-situ target reflectance spectra were resampled to spectrally match with airborne and space-borne imagery. Further, a target region of interest (ROI) was designated for each of the targets in both airborne and space-borne imagery using the known ground position of targets using a GPS device. This article provides a ground to space integrated target detection dataset, including ground positions ROI of the targets, point, and pixel-based in-situ target reference spectra, and the processed airborne and space-borne imagery to make the dataset ready for use. The data acquired in this experiment is an attempt to assess the potential of engineered material target detection in a multi-scale multi-platform view setup. The dataset is a valuable resource for testing and validation of target detection algorithms from various strategic and civilian application perspectives of remote sensing.
Project description:An acute tick-borne rickettsiosis caused by Rickettsia heilongjiangensis was diagnosed in 13 patients from the Russian Far East in 2002. We amplified and sequenced four portions of three rickettsial genes from the patients' skin biopsy results and blood samples and showed that the amplified rickettsial genes belong to R. heilongjiangensis, which was recently isolated from Dermacentor sylvarum ticks in nearby regions of China. This rickettsia, belonging to subgroup of R. japonica, was previously suggested to be pathogenic for humans on the basis of serologic findings. We tested serum samples with different rickettsial antigens from 11 patients and confirmed increasing titers of immunoglobulin (Ig) G and IgM to spotted fever group rickettsiae, including R. heilongjiangensis. Clinical and epidemiologic data on these patients show that this disease is similar to other tick-borne rickettsioses.
Project description:Rickettsiosis is a potentially fatal tick borne disease. It is caused by the obligate intracellular bacteria Rickettsia, which is transferred to humans through salivary excretions of ticks during the biting process. Globally, the incidence of tick-borne diseases is increasing; as such, there is a need for a greater understanding of tick-host interactions to create more informed risk management strategies. Flinders Island spotted fever rickettsioses has been identified throughout Australia (Tasmania, South Australia, Queensland and Torres Strait Islands) with possible identifications in Thailand, Sri Lanka and Italy. Flinders Island spotted fever is thought to be spread through tick bites and the reptile tick Bothriocroton hydrosauri has been implicated as a vector in this transmission. This study used qPCR to assay Bothriocroton hydrosauri ticks collected from Tiliqua rugosa (sleepy lizard) hosts on mainland South Australia near where spotted fever cases have been identified. We report that, although we discovered Rickettsia in all tick samples, it was not Rickettsia honei. This study is the first to use PCR to positively identify Rickettsia from South Australian Bothriocroton hydrosauri ticks collected from Tiliqua rugosa (sleepy lizard) hosts. These findings suggest that B. hydrosauri may be a vector of multiple Rickettsia spp. Also as all 41 tested B. hydrosauri ticks were positive for Rickettsia this indicates an extremely high prevalence within the studied area in South Australia.
Project description:Modelling the spatial spread of vector-borne zoonotic pathogens maintained in enzootic transmission cycles remains a major challenge. The best available spatio-temporal data on pathogen spread often take the form of human disease surveillance data. By applying a classic ecological approach-occupancy modelling-to an epidemiological question of disease spread, we used surveillance data to examine the latent ecological invasion of tick-borne pathogens. Over the last half-century, previously undescribed tick-borne pathogens including the agents of Lyme disease and human babesiosis have rapidly spread across the northeast United States. Despite their epidemiological importance, the mechanisms of tick-borne pathogen invasion and drivers underlying the distinct invasion trajectories of the co-vectored pathogens remain unresolved. Our approach allowed us to estimate the unobserved ecological processes underlying pathogen spread while accounting for imperfect detection of human cases. Our model predicts that tick-borne diseases spread in a diffusion-like manner with occasional long-distance dispersal and that babesiosis spread exhibits strong dependence on Lyme disease.
Project description:Soil moisture content (SMC) is an important factor that affects agricultural development in arid regions. Compared with the space-borne remote sensing system, the unmanned aerial vehicle (UAV) has been widely used because of its stronger controllability and higher resolution. It also provides a more convenient method for monitoring SMC than normal measurement methods that includes field sampling and oven-drying techniques. However, research based on UAV hyperspectral data has not yet formed a standard procedure in arid regions. Therefore, a universal processing scheme is required. We hypothesized that combining pretreatments of UAV hyperspectral imagery under optimal indices and a set of field observations within a machine learning framework will yield a highly accurate estimate of SMC. Optimal 2D spectral indices act as indispensable variables and allow us to characterize a model's SMC performance and spatial distribution. For this purpose, we used hyperspectral imagery and a total of 70 topsoil samples (0-10 cm) from the farmland (2.5 × 104 m2) of Fukang City, Xinjiang Uygur AutonomousRegion, China. The random forest (RF) method and extreme learning machine (ELM) were used to estimate the SMC using six methods of pretreatments combined with four optimal spectral indices. The validation accuracy of the estimated method clearly increased compared with that of linear models. The combination of pretreatments and indices by our assessment effectively eliminated the interference and the noises. Comparing two machine learning algorithms showed that the RF models were superior to the ELM models, and the best model was PIR (R 2 val = 0.907, RMSEP = 1.477, and RPD = 3.396). The SMC map predicted via the best scheme was highly similar to the SMC map measured. We conclude that combining preprocessed spectral indices and machine learning algorithms allows estimation of SMC with high accuracy (R 2 val = 0.907) via UAV hyperspectral imagery on a regional scale. Ultimately, our program might improve management and conservation strategies for agroecosystem systems in arid regions.