Governments and municipalities need to understand their citizens’ psychological needs in critical times and dangerous situations. COVID-19 brings lots of challenges to deal with. We propose NeedFull, an interactive and scalable tweet analysis platform, to help governments and municipalities to understand residents’ real psychological needs during those periods. The platform mainly consists of four parts: data collection module, data storage module, data analysis module and data visualization module. The four parts interact with each other and provide users with a thorough human needs analysis based on their queries. We employed the proposed platform to investigate the reaction of people in New York State to the ongoing worldwide COVID-19 pandemic. I.1https://about.twitter.com/companyNowadays social media is changing people’s life et al. first used machine learning methods to automatically conduct sentiment analysis on the text on Twitter, and added emoticons to the system, which greatly improved the accuracy of the system et al. employed a probabilistic model to classify the text on twitter into polar(tweets with positive or negative sentiment) and non-polar(tweets without sentiments), and then used emotional vocabulary to classify the emotional polarity of polar tweets Since social media is becoming a more and more important part of people’s daily life et al. proposed City Digital Pulse (CDP), a cloud-based heterogeneous data analysis platform. The system collects geo-tagged data from Twitter and Instagram and conducts sentiment analysis on these data et al. presented a multimodal affect and context sensing platform which is designed to enable easy prototyping of novel computer interfaces that sense, respond, and adapt to human emotion Based on the above works, some social media analysis platforms have been constructed. Li The remainder of the paper is organized as follows. In II.1)et al. proposed a lexicon-based method to perform polarity calculation on the multilingual dataset which consists of a mix of reviews in English and Malayalam for sentiment et al. proposed a novel hierarchical neural network model based on dynamic word embeddings (HieNN-DWE) for document-level sentiment classification Document-level sentiment analysis aims to automate the task of classifying a textual review, which is given on a single topic, as expressing a positive or negative sentiment 2)et al. proposed a model which combines a Bidirectional Encoder Representation from Transformers (BERT) with BiGRU to gain the contextualized embeddings before performing sentiment analysis et al. proposed an ensemble method which uses support vector machine with naive bayes features (NB-SVM), an enhanced model to optimize CNN Sentence-level sentiment analysis refers to the process of identifying the sentiment polarity of a single sentence. Many feature-based statistical methods, such as Naive Bayes (NB), Random Forest (RF) and Support Vector Machine (SVM) were employed to solve this problem and achieved high accuracy in classifying sentiment type in the past 20 years. Recently, models based on deep learning methods have made progress in this area. In 2019, Shen 3)et al. proposed the aspect-level sentiment capsules model (AS-Capsules), which could perform aspect detection and sentiment classification at the same time et al. proposed an interactive rule attention network (IRAN) considering the influence of grammatical rules Aspect-level sentiment analysis is designed to solve the problem when multiple aspects show up in a complex sentence which is quite common in the real world. Different from the other two categories of methods, aspect-level sentiment analysis needs to discover all the aspects involved in the text first and then perform sentiment analysis for each aspect. Wang Generally speaking, analyzing human affective states involves three steps: sentiment analysis, emotion detection, and human need detection. The first step is sentiment analysis, also known as opinion extraction, is the computational treatment of opinions, sentiments and subjectivity of text are employed et al. gathered large scale data from social media and proposed a novel Deep Learning based approach to detect emotions including happy, sad, and angry in texts et al. proposed a Knowledge-Enriched Transformer (KET) to understand human emotions by using a context-aware affective graph attention mechanism Meanwhile, textual emotion detection, whose task is to classify a text into one or more predefined emotion categories by extracting the emotional elements in the textual content, has gained a lot of attention in recent years. The emotional classification methods mainly include dictionary-based methods, rule-based methods, machine learning-based methods, composite methods, and multi-label methods III.A.As shown in B.2https://scrapy.org/Since the standard Search API of Twitter allows developers to collect tweets published in the past 7 days, we made our own crawler based on it to collect recent data. However, Twitter does not provide developers with an API to download historical data. Therefore, we designed a historical data crawler as a supplement in case old data is required. The crawler is built on Scrapy, an open-source web-crawling frameworkC.We built our database based on Mongodb, a dynamic and scalable NoSQL database as it can provide high performance when processing Big Data. As our platform needs to support a small number of write operations but a large number of read operations, we built a replica set in Mongodb for the original database which has a primary node and multiple secondary nodes to scale out read operations. As D.We employed a human need-detection framework introduced in 1)The tweets we downloaded from Twitter are stored in a JavaScript Object Notation (JSON) format, where each tweet consists of dozens of key-value pairs. As we focused on analyzing only the textual content, we obtained all the texts using the key “text.” In the online phase, we followed the same offline data preprocessing steps presented in 2)Feature extraction is the process of removing a list of words from the text data and then transforming them into a feature set usable by a classifier. In other words, a tweet needs to be converted to a vector that can represent the tweet. From each tweet, we extracted the text-based features, psychological features, and Twitter-specific features developed during the offline phase 3)Because the vectors that we constructed to represent tweets are composed of features from text-based, psychological, and Twitter-specific three different aspects, the values in vectors have various ranges. Features with bigger ranges may have a bigger influence on the classification result. To ensure that we capture the accurate information, we employed Min-Max scaling: 4)For the human need classification models developed in E.We designed a user-friendly interface to interact with users and visualize the analysis result. The interface is built on Chart.js which is a free open-source JavaScript library for data visualization. Users need to register for accounts on the register page  first anIV.A.3https://www.cdc.gov/We inspected the reaction of people in New York State to the ongoing worldwide COVID-19 pandemic. The first case of COVID-19 in New York was confirmed on March 1. As of April 6, 2020, there have been over 130000 confirmed cases in the state, and of those 4159 people have died with the highest number of confirmed cases of any state in the United States.B.•I feel like this a great time to identify 1 or 2 people as your primary partners until this Corona Virus dies down. – Satisfied relatedness need•I won’t be hanging my white friends till Corona virus over.-Dissatisfied relatedness need•Yeah I get it, the flu has killed waaaay more people than the Corona Virus. But as a mother to young children I AM going to stress about the virus the same way I stress about the flu. If it has the possibility to KILL my children, I’m gonna worry. So shut the fuck up about it.-Satisfied autonomy need•I think I got the corona virus and need to go home to isolate myself.-Dissatisfied autonomy need•I have a better chance of listening to country on my own than getting the corona virus.-Satisfied competence need•Why would we expect Trump and the GOP to do anything to protect our health from the corona virus or anything else when they have already depleted the EPA? They have rolled back 95 EPA protections endangering the environment and American lives.-Dissatisfied competence need•BREAKING NEWS: Peter Griffin has tested positive for Corona Virus. Send prayers for him and his family. – Satisfied relatedness need•I’m actually terrified for my kids to get this corona virus going around! Especially my baby because she’s so young! -Dissatisfied relatedness need•Can’t wait to see what happens after the corona virus pandemic is over. -Satisfied autonomy need•Looks like I may have lost my job thanks to the corona virus. -Dissatisfied autonomy need•Can’t believe stony brook is switching to all online classes in preparation for the corona virus that’s so crazy but smart. -Satisfied competence need•We do not have access to Corona tests, these numbers are not accurate. Not only is prevention and treatment the key to this PANDEMIC (worldwide) but knowledge is power. You are failing our children and our city. #besmart. -Dissatisfied competence needIn week 2, as can be seen from •can’t wait for my kid to come home one day and show me he’s reading “ I Survived: The Corona Pandemic of 2020”. – Satisfied relatedness need•My best friend can’t even come to my “closest friends only” baby shower because of the stupid corona virus. -Dissatisfied relatedness need•after the corona virus calms down, i will start living my best life with or without the attendance of others. -Satisfied autonomy need•So if this corona virus thing keeps getting out of hand. I’ll be quitting my job and I’m going quarantine myself at James Franco’s house. -Dissatisfied autonomy need•I told myself I wasn’t going to go out this weekend. Thanks corona virus for helping me accomplish my goals. -Satisfied competence need•i’m so over this corona virus. i just want to participate in my extracurricular and then graduate. every other high schooler except c/o 2020 had that chance. what did we do:! -Satisfied autonomy need•Corona virus is so trash…. I was supposed to start swimming classes this weekend. -Dissatisfied autonomy need•My move in date for my first apartment keeps getting pushed back…I’m about to find a cure for this corona virus myself. -Satisfied competence need•I have lost my job a week before the corona virus shut down and applied for unemployment and was denied immediately. I then found a new job being an assistant teacher at a daycare but once the mayor ordered for schools to close then that meant my job closed so I couldn’t start. -Dissatisfied competence needFrom •With everything that is going on with the Corona virus. I was glad that my friend decided to check up on me and my family last night. We need all of the love and support at this moment. – Satisfied relatedness need•Trump downplayed the corona virus for months. Called it the latest democrat hoax, said we have 15 cases that will soon be 0, how can you possibly defend this obvious mismanagement? -Dissatisfied relatedness need•Good Morning! Its Monday, Rise and Grind! Don’t let that bitch Corona stop you from accomplishing something today. Big or small goal, today YOU got it! (Cute kitten to make monday better) #MotivationalQuotes #Covid-19. -Satisfied autonomy need•I just spent a literal hour, calling different agencies. Local and state, trying to find a place where I can report a potential corona virus violation of the Governors order to do my part as a civilian and have it looked into and got nowhere. -Dissatisfied autonomy need•This Corona Virus is just a setback I’m still striving to achieve my goals for this year. – Satisfied competence need•The CDC has been warning us about a future pandemic we were unprepared for. Trump cut funding to CDC and scientific research into diseases in the past and while Corona Virus is not Trumps doing, his policies made it harder for us now. -Dissatisfied competence needAs the number of confirmed cases of coronavirus in New York State had gotten to over 130000 with 4159 people died in week 5, satisfaction levels, shown in C.•My mom is now scared of the Corona virus in NY so no vacation for me cause I’m not about to go alone! – Family•We have many difference of opinions, even with our own friends, but when it comes to a common enemy, we have to put our difference of opinions aside and join our hands to fight together to extinct deadliest Virus than #Corona & save future. #Maridhas #Rajinikanth. – Social Relation•I might go to work even if I get the corona virus. – Work•My school just cancelled classes for next week due to the Corona Virus. #CoronaOutbreak. – Education•Where can I get a free corona test Mr. President because your director of the CDC says I can get one but I’ve made several phone calls and I can’t get one. – Government•i don’t know how i feel about planning a trip to vegas in may during this whole corona virus thing. – Leisure•Can’t wait till this corona virus is over so I can stop washing my hands every time I go to the bathroom. – Health•All my friends. My birthday was Tuesday March the 10th, but I’m extending because of the Corona virus, so I’m accepting presents over the next two weeks until the 25th of March, just wanted to let everybody know. – General Life•Everyone please pray for my family. My mom got the corona virus. – ReligionThe analysis result shows that, throughout this period, the most pronounced human need in these tweets is relatedness with 47.42%, followed by autonomy with 16.63% and competence with 14.51%. As can be seen from •My group chat is having a very detailed conversation about the corona virus, I’m glad I’m friends with smart people.-Supportive social context•FOR CORONA VIRUS stay home make yourself happy and do something I’m cooking every day good and healthy food, and I share to help you.The best time to learn anything for your self is now FOR CORONA VIRUS.-Supportive social context•If my last semester at college is me taking online classes because of corona virus I will go into a depression.-Unsupportive social context•My job really sent me home because they think I have corona virus I’m dead.-Unsupportive social contextFor social context analysis, V.In this paper, we propose NeedFull, an interactive and scalable tweet analysis platform, which mainly consists of four main parts: data collection module, data storage module, data analysis module and data visualization module. The four parts interact with each other and provide users with a thorough human needs analysis based on their queries. This awareness of people’s affects is a crucial step for governments and municipalities to understand their citizens’ psychological needs especially in critical times and dangerous situations. However, the human need detection model we employed can only analyze text contents. That is also the reason we cannot extend our platform to Instagram where people only share images. For future work, we plan to extend the platform with human needs analysis of other social media contents such as image and video.


Mytilus edulis and M. trossulus. These ecologically, stratigraphically and economically important molluscs co-occur and hybridize in many areas of the North Atlantic and the neighboring Arctic. Any cues for distinguishing them in sympatry without genotyping would save much research effort. Recently these species have been shown to statistically differ in the White Sea, where a simple character of the shell was used to distinguish two mussel morphotypes. In this paper, we analyzed the associations between morphotypes and species-specific genotypes based on an abundant material from the waters of the Kola Peninsula  and a more limited material from Norway, the Baltic Sea, Scotland and the Gulf of Maine. The performance of the “morphotype test” for species identification was formally evaluated using approaches from evidence-based medicine. Interspecific differences in the morphotype frequencies were ubiquitous and unidirectional, but their scale varied geographically . In addition, salinity-related variation of this character within M. edulis was revealed in the Arctic Barents Sea. For every studied region, we established relationships between the proportions of the morphotypes in the populations as well as between the proportions of the morphotypes in samples and the probabilities of mussels of different morphotypes being M. trossulus and M. edulis. We provide recommendations for the application of the morphotype test to mussels from unstudied contact zones and note that they may apply equally well to other taxa identified by semi-diagnostic traits.Cryptic and hybridizing species may lack diagnostic taxonomic characters leaving researchers with semi-diagnostic ones. Identification based on such characters is probabilistic, the probability of correct identification depending on the species composition in a mixed population. Here we test the possibilities of applying a semi-diagnostic conchological character for distinguishing two cryptic species of blue mussels,  Mytilus edulis and M. trossulus are old evolutionary lineages of Pliocene origin . We used generalized linear (mixed) models, GL(M)Ms, with binomial distribution and a logit link-function. All GLM models were constructed with glm function from the package “stats” [R_2019] whereas GLMM were fitted with glmer function from the package “lme4” . The val2  and takes the value Delta = 0 when both samples are pure M. edulis (Ptros1 = Ptros2 = 0) or pure M. trossulus (Ptros1 = Ptros2 = 1), Delta = 0.5 when both samples are equivalent mixtures of two species (Ptros1 = Ptros2 = 0.5) and Delta = 1 when one sample represent pure M. trossulus (Ptros1 = 1) and another pure M. edulis (Ptros2 = 0).We considered all 630 possible pairwise combinations of samples from the P(T|tros), P(T|edu) and PT were obtained from pooled data on each pair of samples and used for calculation of predicted values of P(edu|E) and P(tros|T) basing on Eqs Ptros  with the step 0.01  and predicted values of Ptros basing on PT  with the step 0.01 .  and P(tros|T) obtained by Eqs Ptros obtained by Estimates of  Ptros 0; with the Ptros 0; with theP(T|edu) and P(T|tros) as parameters of Eqs PT and predictions from Eqs Ptros. These predictions were visually compared with those from regression Model 4 and Model 6, respectively.Goodness indices for each pair were plotted against the corresponding Delta values and the LOESS regression curve was fitted to find associations between them. Depending on the results of the analyses, we determined which combinations of samples could be used for predictions with best results. Best combinations of samples from each set were used to assess Ptros by PT calculator” which assumes that samples with the highest and the lowest PT in regional sample sets do represent, respectively, pure M. trossulus and pure M. edulis and that morphotype frequencies in these samples could be directly used as parameters P(T|tros) and P(T|edu) of Ptros values predicted by the calculator for samples from different sets were visually compared with empirical ones.Additionally, we tested the “lazy Ptros by PT” and “genotype by morphotype” probability calculators implementing Eqs https://polydora.shinyapps.io/Calculator/.For illustrative purposes and for the convenience of potential users of the “morphotype test” or any similar semi-diagnostic tests we provide the online “The studied binary morphological character was previously defined as the “presence/absence of a distinct uninterrupted dark prismatic strip under the ligament”, based on material from the White Sea only , 22. In Therefore, we amend the description of the T/E morphotype character as follows: the presence/absence of an uninterrupted strip of the prismatic layer under the ligament nympha clearly recognizable by a scar separating the strip from the nacreous layer of the rest of the shell. This description was applicable to all the mussel samples examined in this study.M. edulis and M. trossulus within and between contact zones revealed in the study is illustrated in P(T|edu) and P(T|tros)  in pooled samples from different sets are provided. P(T|edu) was 0.53 in the saline Barents Sea (BH) and less than 10% in all the other sets. In its turn, P(T|tros) was 0.17 in BALT, 0.42 in NORW, 0.49 in the GOM and more than 0.75 in WSBL and SCOT. P(T|tros) estimates in Norway and the Gulf of Maine were much affected by the few outlier samples (see below). If we discard these samples, P(T|tros) will make up 0.54 in Norway and 0.71 in the Gulf of Maine.Variation in morphotype frequencies between M. trossulus in the Pacific, the populations were nearly monomorphic for the T-morphotype. In the Passamaquoddy Bay P(T|tros) was 0.81, i.e. close to that in most of M. trossulus populations in the Gulf of Maine. All reference M. edulis populations from temperate areas  were nearly monomorphic for the E-morphotype. At the northeast extreme of the species range in eastern Atlantic, in the southwestern Barents Sea, P(T|edu) varied considerably between the samples, in particular between the samples from brackish (range 0–3%) and saline (0.35–0.70%) localities (see P(T|edu) was also recorded in two northernmost samples from western Atlantic, Greenland (0.66) and the Gulf of Saint Lawrence (0.73).ties see , as it dM. trossulus (Ptros) and the frequency distributions of q-values at 10% intervals (E- and T-morphotypes are indicated) in different contact zones are provided in the GOM, SCOT, WS, BL and BH, with most of the mussels having low (q<0.2) or high (q>0.8) q-values  and less than 15% having intermediate values (putative hybrids). However, the distributions were more flattened in NORW and BALT . PT positively correlated with q-values in each set (M. trossulus-dominated populations (high Ptros) than in M. edulis-dominated ones  and q<0.5 (genotypes dominated by M. edulis genes), as well as between subsamples with q>0.8 and q>0.5 (putative purebreds of M. trossulus and genotypes dominated by its genes) in the samples were close to 1:1 (Relationships between e to 1:1 .M. trossulus” (q>0.5) and “M. edulis” (q<0.5). (1) These categories should be interpreted as admixed genotypes dominated by genes of one of the species in NORW and BALT and as purebreds in the other contact zones. (2) Morphotype frequencies in hybrids are intermediate between those in parental species, yet in not considering hybrids as a separate class we only slightly bias interspecific differences.Based on these results, two caveats should be made before embarking upon the analyses based on comparison of “PT, P(T|tros), P(T|edu), P(tros|T), P(edu|E) as functions of Ptros in samples from the White Sea (WS), the brackish Barents Sea (BL) and the saline Barents Sea (BH) are visualized in Variation patterns of M. trossulus (Ptros) and the proportions of T-morphotypes (PT) in samples was revealed for all the three sample sets ) and M. trossulus (P(T|tros)) against proportions of M. trossulus in samples (Ptros) revealed the following patterns . In BH it was rather weak (expected differences 0.18 for Ptros = 0.5) due to an increased P(T|edu) but significant  and P(T|edu) with Ptros was found in all the three subsets. This means that with the increasing contribution of M. trossulus to the samples the frequencies of T-morphotypes increased both among M. edulis and among M. trossulus.The analysis of the frequencies of T-morphotypes in subsamples of Model 2, , Fig 3. M. trossulus by the T-morphotype (the frequency of M. trossulus among T-morphotypes (P(tros|T)) expectedly increased with the increasing Ptros, while the probability of correct identification of M. edulis by the E-morphotype (P(edu|E)) demonstrated an opposite pattern  tended to one (any mussel with a T-morphotype is 100% M. trossulus), while P(edu|E) tended to zero (any mussel with an E-morphotype is 100% M. trossulus), and vice versa. In the well-mixed samples (Ptros = 0.5) the predictive values for both species were about 0.75–0.85 in WS and BL but only 0.60–0.70 in BH . The statistical analysis indicates that both P(tros|T) and P(edu|E) predicted by the model were smaller in BH than in WS and BL.The probability of correct identification of Model 3, , Fig 3. 2 were close to each other (Sample) as regulator of models was weak, i.e. the reproducibility of the results in different populations was satisfactory.For each of the GLMM models considered (Model 2 and 3), marginal and conditional pseudoRch other . This inWS and BL, while BH was always different from WS  and BH showed the lowest AIC (AIC = 2172.7). Therefore, in the following analyses we will consider two sets, WSBL and BH.In comparisons between sets, the regression coefficients did not differ statistically for  from WS . To assePtros variation against PT and the patterns of P(T|tros), P(T|edu), P(tros|T) and P(edu|E) variation against Ptros in samples from different geographical zones are visualized in WSBL and BH sets) together with the data from other regions revealed the same patterns as those described above. Again, in all the cases when mixed models were used  as regulator of models, i.e. a satisfactory reproducibility of the results from population to population in all the regions.The patterns of M. trossulus in samples (Ptros) was positively correlated with the proportion of T-morphotypes (PT) in the other sets, as it did in the samples from the White and the Barents Sea. This tendency was significant for all the sets  as compared with the Ptros range (~0–1), and the small surplus of T-morphotypes in the samples was accompanied by a strong increase in the M. trossulus prevalence. A similar tendency was observed in the scanty material from NORW. Both SCOT samples fell on the Y = X line. Noteworthy are a few “outlier” samples from GOM and NORW, in which PT was close to zero but Ptros was high.The proportion of the sets . OtherwiM. edulis (P(T|edu)) were low everywhere but in BH, frequencies of T-morphotypes in M. trossulus (P(T|tros)) demonstrated a strong variation among sets and a noticeable variation within some sets  (While frequencies of T-morphotypes in ome sets . Similar(T|tros) .P(tros|T) and P(edu|E) on Ptros in GOM, BALT and NORW (Model 6. P(tros|T) increased with the increasing Ptros, while P(edu|E) showed an opposite tendency. To simplify and formalize the comparison, we provide the predictions of Model 6 for equally mixed populations (Ptros = 0.5) together with their 95% confidence intervals in M. trossulus among T-morphotypes (P(T|tros)) and M. edulis among E-morphotypes (P(T|edu)) in pooled samples from the respected sets are also provided.The pattern of dependence of Model 6.  was the Model 6. : P(tros|P(edu|E) in BALT did not differ significantly from 0.5, which corresponds to an equal probability of correct and incorrect identification. At the same time, the probabilities of correct identification of M. trossulus by the T-morphotype in GOM, BALT and NORW were quite high (for the range of Ptros≥0.5). In general, the highest predictive values for both species were revealed in WSBL.For equally mixed populations the predictive values of Ptros) and the probability of correct species identification (P(tros|T), P(edu|E)) using the morphotype test  in four cases for M. edulis and in four cases for M. trossulus, but only in one case when the correction for multiple testing was applied  in 16 out of 34 informative comparisons (when species-specific genotypes were both present and polymorphic for morphotypes) for Ptros by PT calculator”) using as an input for assessment of equations parameters (P(T|tros), P(T|edu)) the data on all possible pairs of samples from WSBL and compared the values predicted by these equations with those predicted by regression Models 6 and 4, respectively (We applied Eqs ectively .Ptros were obtained when the most dissimilar samples consisting of nearly pure M. edulis and M. trossulus (Delta >0.75) were taken for P(edu|E) and P(tros|T) values were obtained when the most mixed samples  were taken for Eqs Ptros using “Ptros by PT calculator” one should use the most dissimilar samples to assess P(T|edu) and P(T|tros) as calculator parameters. In order to predict P(edu|E) and P(tros|T) using “genotype by morphotype calculator” one should assess the parameters using the most mixed samples. However, the Ptros as input in Eqs WSBL, BH, GOM and BALT we used pooled sets of samples with Ptros <0.1 and >0.8 to calibrate “Ptros by PT calculator” and 0.45 < Ptros < 0.65 to calibrate “genotype by morphotype calculator” as described above  predictions in WSBL for Ptros<0.25 and P(edu|E) in GOM for Ptros>0.6 i.e. in the Ptros ranges corresponding to a small prevalence of the species.As for the “genotype by morphotype calculator”, the predictions generally were in good correspondence with the regression lines . Deviations were observed for Ptros by PT calculator”, in which the highest and the lowest PT in samples from regional sets are used as P(T|tros) and P(T|edu) parameters of WS, BL and GOM correspondence between the observed and the predicted Ptros values in samples was generally good. In BH, Ptros was slightly overestimated by the calculator due to the absence of pure M. trossulus samples in the data and the formal choice of a numerically small .An exercise with the “lazy M. edulis and M. trossulus genotypes in the White Sea differed by the frequencies of the shell morphotypes [M. trossulus and M. edulis. These relationships could be used for a reliable prediction of the taxonomic structure of any population in the White Sea. Moreover, any mussel in an equally mixed population could be identified as M. trossulus or M. edulis with the accuracy of about 80%  of any given mussel. In the light of this, our finding that photypes  seemed vphotypes , 44 but photypes  and deriM. edulis and M. trossulus by the morphotype was a “privilege” of the researchers working at the White Sea or whether this approach could be used for identification of these two species worldwide. Though our data on the contact zones between the species outside northern Russia were limited, our results indicate that this approach may be useful everywhere since interspecific differences in the morphotype frequencies were ubiquitous and unidirectional. However, its utility is evidently different for different contact zones.The ultimate goal of our study was to find out whether the possibility of identifying An evident limitation of the morphotype test in the contact zones with extensive hybridization such as the Baltic Sea and Western Norway is that hybrids, which are quite numerous and ecologically important, are considered together with the closest purebreds. At the same time, since hybrids are intermediate in morphotype frequencies between the species [; this stThough the hypotheses that different mussel species may differ by the extent of the nacreous layer development under the ligament nympha was already suggested by Zolotarev, Shurova  and VervM. trossulus and M. edulis was suggested by Beaumont et al. [M. edulis plantations were genetically similar to M. trossulus. The fragile mussels differed from M. edulis  by a combination of shell traits including shape, the degree of expression of growth ridges and the color of the inside. The promising identification method was however not developed further. A comparison of the photographs of shells in Beaumont et al. [To note, another method for a fast morphological diagnosis of t et al. , who shot et al.  with ourWe will start with the discussion of the patterns of variation of the morphotype frequencies revealed in our study. Then we will discuss the applicability of the morphotype test in different contact zones. In the closing section, the limitations of single-marker taxonomic tests for blue mussels and other taxa will be outlined.M. edulis from the temperate seas  were nearly monomorphic for the E-morphotype, while the northern samples were more polymorphic and diverse. In turn, the reference populations of M. trossulus from the northwestern and northeastern Pacific (Washington) were nearly monomorphic for the T-morphotype. Nevertheless we cannot necessarily exclude the possibility of geographic variation in M. trossulus in its ancestral Pacific range or confirm that the T-morphotype is the “ancestral” state for this species. Zolotarev [M. trossulus from Oregon (northeastern Pacific).Some variation in the morphotype frequencies was observed among putatively pure conspecific populations sampled at a distance from the contact zones. Samples of pure olotarev  identifiolotarev ) and fouM. trossulus the morphotype frequencies varied between the contact zones, and elevated frequencies of E-morphotypes were found in Norway and, especially, in the Baltic Sea. The variation within contact zones was mostly due to the few “outlier” samples from the Gulf of Maine and Norway. On the contrary, M. edulis showed little variation between zones, the T-morphotype being universally rare. In a notable exception the T-morphotype frequency was clearly elevated (up to 40%) in samples from saline localities (> 30 ppt) in Kola Bay and surroundings. Similar salinity-related variation was found in M. edulis from the more eastern areas of the Barents Sea, at some distance from the contact zone between these species along the Kola Peninsula coast.In M. edulis and among M. trossulus genotypes with the increasing prevalence of M. trossulus in the samples.Finally, an analysis of the abundant material from the White and the Barents Sea demonstrated how the morphotype frequencies varied with the taxonomic composition of the mixed populations. The frequencies of the T-morphotype increased both among M. trossulus from the Baltic Sea and Norway were characterized by extremely high frequencies of the E-morphotype. Two hypotheses, which are not mutually exclusive, can be offered to explain this phenomenon. One hypothesis links the morphotypes to species-specific genes that can introgress between species as a result of extensive hybridization and backcrossing. The Baltic M. trossulus is stronger introgressed by M. edulis genes than any other Atlantic population [M. edulis x M. trossulus hybrid swarm, which is fundamentally different from the “oceanic” M. trossulus [M. trossulus populations can be strongly introgressed by M. edulis genes too [pulation , 33. Dueenes too .M. trossulus is reduced under the influence of some environmental factors, both micro- and macro-geographical. We suspect that the nearly zero frequencies of the T-morphotype in the “outlier” samples  frequencies of the E-morphotype and the more Arctic populations with lower frequencies of the E-morphotype in oceanic habitats runs somewhere between North Cape and the Kola Bay (http://esimo.oceanography.ru/).While local factors putatively affecting morphotype frequencies in Kola Bay . This arThe functional significance of the morphological character underlying the E- and the T- morphotype (the presence/absence of the nacreous layer under the ligament) is unclear. However, we suspect that the morphotypes might differ in conspecifics by the degree of development of the nacreous layer itself and thus in the thickness and strength of the shell. The nacreous shell layer is mechanically the strongest .Can we expect the shell thickness and structure to differ in mussels from saline (oceanic) and brackish (estuarine) environments in the Arctic? Apart from the low temperatures, the Arctic Sea is characterized by a reduced concentration of calcium carbonates  and, seaM. edulis from the brackish and the saline localities in the Arctic is that in the estuaries the mussels allocate more energy for shell maintenance thus keeping their nacreous layer thick while in less corrosive but more famished oceanic habitats they allocate more energy for somatic growth keeping their nacreous layer thin. As a result, the majority of M. edulis from the saline localities has the undeveloped nacreous layer. It is noteworthy that in the areas where M. edulis demonstrated salinity-related variation, the morphotype frequencies in M. trossulus varied negligibly. This could be attributed to a generally lower shell plasticity in “oceanic”  M. trossulus than in M. edulis in response to the environmental stressors  and the “Ptros by PT calculator” , while in the saline areas in the Barents Sea it did so only for M. edulis mussels.The possibility to identify individual mussels by the morphotype seems to be the “privilege” of researchers working at the White Sea and brackish environments of the Barents Sea. The morphotype test also seems to be promising for individual assignment in the Gulf of Maine, except in the outlier samples (see above) and, possibly, in Scotland . In the Baltic Sea and Norway the morphotype test worked reliably only for M. trossulus or M. edulis or control genotyping of mussels from the populations of interest. Still, it is noteworthy that the accuracy of individual identification of mussels could be approximated basing on the morphotype frequencies in three “calibration” samples  and Eqs We would like to stress that, if one plans to use the morphotype test for individual assignment, reliable genetic references are indispensable. These could be either empirical relationships between the proportions of the morphotypes in the samples and the probabilities of mussels of different morphotypes being M. trossulus by morphotypes in some populations, such as those in Norway and the Gulf of Maine, which were the sources of the “outlier” samples. Another is the bias generated by a non-random association of morphotypes with size (or age) of conspecific mussels such as was observed in very rare (about 2%) samples. A further risk are uncertainties in the application of the test to populations from intermediate salinities (about 30 ppt) in the Barents Sea.The morphotype test comes with pitfalls. One of the evident risks is an underestimation of P(species|trait) = 1. However, in practice the probability can be lower for two reasons. First, because of scoring errors related to the researcher’s skills or the defective condition of the specimen. Second, for the ambiguity in the diagnosticity of a trait. It is generally impossible to determine whether diagnostic characters are indeed fixed if the sample size is finite [P(species|trait) ≤ 1.Traditional species identification relies on diagnostic (fixed) morphologic traits of the organism, usually included in the diagnosis. In the terms of the probability theory, it means that the probability of an individual with a species-specific diagnostic marker being a representative of the species in question is equal to one: s finite . Hence, Some taxa, however, lack diagnostic characters and have to be identified on the basis of semi-diagnostic ones. This is the case with the blue mussels . In caseM. edulis and M. trossulus is different in contact zones in western Atlantic (i.e. the Gulf of Maine) and the Baltic Sea [M. edulis genes into the local M. trossulus genome [M. edulis–M. trossulus contact zones, though some attempts have been made . Th. ThM. edct zones , 59. On M. edulis and M. trossulus is certainly uncommon in taxonomy. At the same time, it is not unique. There are other taxa, which lack fixed diagnostic morphological characters and are identified by semi-diagnostic traits, individual or complex such as like the coordinates of multifactorial analysis. These taxa include subspecies defined according to the 75% rule [A situation when one has to rely on a singular “informal” semi-diagnostic character to distinguish morphologically such old evolutionary lineages as 75% rule , cryptic75% rule  and hybr75% rule . TherefoS1 FigM. trossulus (right) and M. edulis (left) genotypes from the Kola Bay  or partially (B) covered by the nacre. C, D. T-morphotypes: a strip of uncovered prismatic layer under the ligament nympha is dark and wide  or pale and narrow, recognizable by a scar separating it from the nacreous layer . E. External and internal features of the shell valves of (TIFF)Click here for additional data file.S2 FigPtros (proportion of M. trossulus). Red and blue dots indicate T- and E-morphotypes, correspondingly. To avoid overplotting, the horizontal position of all points  was jittered by adding a small random value. For visual purposes, chart areas with maximal dots density are contoured and the probability of T-morphotype presence is shown by the color gradient. The contour lines represent the kernel density estimations  with density2d function in “ggplot2” package. The probability was assessed using the binomial general additive model, GAM  with the binary outcome (T vs E morphotype) as dependent variable and “Structure q-score”, “Ptros” and “Set” as independent predictors. SCOT and NORW were not included in GAM due to poore cover of Ptros axis. References for A. Frequency distributions of individual q-values in pooled samples. Red and blue bars indicate T- and E-morphotypes, correspondingly. B. Distributions of individual q-values in samples ordinated by (TIF)Click here for additional data file.S3 FigM. edulis. B. M. trossulus. Samples from different zones are shown in different colors.A. (TIF)Click here for additional data file.S4 FigDots–estimates, solid line–linear regression, dashed line–Y = X line.(TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(PDF)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.


Viral infections are the most common among diseases that globally require around 60 percent of medical care. However, in the heat of the pandemic, there was a lack of medical equipment and inpatient facilities to provide all patients with viral infections. The detection of viral infections is possible in three general ways such as (i) direct virus detection, which is performed immediately 1–3 days after the infection, (ii) determination of antibodies against some virus proteins mainly observed during/after virus incubation period, (iii) detection of virus-induced disease when specific tissue changes in the organism. This review surveys some global pandemics from 1889 to 2020, virus types, which induced these pandemics, and symptoms of some viral diseases. Non-analytical methods such as radiology and microscopy also are overviewed. This review overlooks molecular analysis methods such as nucleic acid amplification, antibody-antigen complex determination, CRISPR-Cas system-based viral genome determination methods. Methods widely used in the certificated diagnostic laboratory for SARS-CoV-2, Influenza A, B, C, HIV, and other viruses during a viral pandemic are outlined. A comprehensive overview of molecular analytical methods has shown that the assay's sensitivity, accuracy, and suitability for virus detection depends on the choice of the number of regions in the viral open reading frame (ORF) genome sequence and the validity of the selected analytical method. Viral diseases are infections caused by different types of viruses. Viruses are structures of various microscopic sizes (from 20 to 900 nm) and morphological forms, composed of genetic material, which can be positive or negative sense, single (ss) or double-stranded (ds) deoxyribonucleic acid (DNA) or ribonucleic acid (RNA), surrounded by a coating based on proteins, glycoproteins, or lipids . VirusesViruses constantly attack humankind. Over the last two centuries, a viral pandemic has posed an increasing threat to public health worldwide. From 1889 to the present, there have been several viral pandemics throughout human history. 1889–1890 the Asiatic flu pandemic killed about 1 million people worldwide , 3. 1918The Asiatic flu pandemic of 1889–1890 was quickly and in detail defined in the media of all the affected countries , and publications were mentioning not only statistics but also the symptoms of the disease and the strategy used to manage the pandemic. The origin of the Asiatic flu pandemic virus is still unknown, but it is hypothesized that the pandemic could be caused by the H3N8 virus , 12 or Hthe release of virus or it’s genetic information from a particular matrix type,the development of molecular and non-molecular virus detection methods,the improvement of bioanalytical methods for the determination of specific antibodies against viral proteins and other virus-related structures.In the face of a pandemic, various technologies and strategies are being developed, focusing on an accurate diagnosis of a particular disease, epidemiological control security, and effective prevention of virus spread. Scientists, diagnostic, and pharmaceutical companies are working hard and collaborating to detect infections faster, more accurate, and cheaper. Therefore, it is essential to know virus sequences and molecular data to apply optimal virus detection methods. Virus detection methods must be of high quality, sensitivity, specific, and relatively simple in function. Analytical virus detection methods, general-purpose reagents, or equipment must be manufactured and validated following the regulatory compliance and quality assurance (QA) rules of the International Organization for Standardization (ISO) , 23. TheThe work aims to describe the validated methods used in the world market to detect SARS-CoV-2, Influenza A, B and C, HIV, and other viruses, to determine the dependencies of the methods and results, to provide insights.Viral RNA is purified from tissue or blood samples. Reverse transcription reaction is performed to obtain cDNA  from virGenetic material is amplified by polymerase chain reaction (PCR). The data analysis is performed. The entire process takes more than 2 h .With experience from previous pandemics and other infections, it is possible to respond correctly to the spread of some viruses. The global COVID-19  pandemicSome alternative innovative technological solutions are being sought to maintain the sensitivity of real-time PCR but to shorten the time from sampling to detection. However, to eliminate the gel electrophoresis step in analytical methods, DNA fragments can be identified by DNA sensors –34. EvenUnfortunately, the choice of virus or disease detection method depends on many factors such as the nature of the virus, the affected area, the activity and viability time on different surfaces, or the virus incubation period Fig.  35]. As. As35]. Virus detection methods can be divided into two groups Fig.  moleculaThe first discovered virus was the tobacco mosaic virus (TMV) in 1882, invented by Iwanowski . He and Transmission electron microscopy (TEM) is the only technique that can provide simple, fast, and clear morphological images of the virus  and diff6–107 particles/ml [The minimum virus concentration required for successful morphologic identification by TEM is about 10icles/ml . Since ticles/ml , 111. Wiicles/ml , 113,  and the number of total particles (whether or not they are infectious) of all these viruses by TEM helped to more accurate classification of viruses. The main disadvantages of virus detection by the TEM method are particle counting—when counting manually in several grid elements simultaneously, this method is not very accurate. However, by TEM technique can incorrectly identify viruses with similar morphology. However, the advantage of the TEM method is its affordable application to "dirty" clinical samples such as plasma, urine, feces, or to detect the growing virus using cell culture . TEM turns out to be necessary to detect and identify a new  in hydrated biological material (sample thickness ⩽ 10 microns) . The useComputed tomography is another tool that describes a fast scan time and a clear image for treating various viral diseases. Unfortunately, there are changes in the organs as the viral illness progresses. In the early stage, pneumonia –139 showThe simplest way to detect a viral infection is to monitor physiological properties. Fever, dry cough, nasal congestion, runny nose, sore throat, myalgia, and fatigue are the main manifestations of respiratory . These methods were widely used only in virology research laboratories for virus investigation due to their sensitivity.Molecular diagnostic methods are used to (i) detect antibodies to different viral proteins or (ii) to directly detect the whole virus or its components. The first molecular diagnostics methods became available in the 1970s when scientists began using recombinant DNA technology (constructed DNA probes) for virus detection , 156. ReDetection of viral infection by serological (blood) tests allows the detection of virus type, subtype, viral load , drug resistance, and how long the organism has been infected with the pathogen. Moreover, blood samples can be stored for long periods and remain relatively stable. Plasma or serum is usually stored refrigerated or frozen for long-term storage, and dried blood stains remain stable at room temperature. Many viruses are excreted in large amounts in urine or saliva, so non-invasive samples  are alsoNucleic acid amplification procedures, including PCR, real-time PCR PCR , RT-PCR n, where n is the number of cycles. Astonishing, using PCR or real-time PCR method, the 105–106 copies of DNR can be made in 25–30 cycles within ~ 2–3 h. In RNA viruses, double-stranded DNA is prepared by cDNA technique using oligonucleotides and reverse transcriptase in the reaction. Real-time PCR is known to be more sensitive, faster, and much easier to perform when compared to conventional PCR by  real-time RT-PCR study of RNA viruses was performed by Osman et al. The authors [Nucleic acid amplification is a straightforward technique for rapidly amplifying billions  of DNA c authors  used man authors –205.As mentioned earlier, the nucleic acid amplification technique requires generating and constructing one or two sequences directed to regions of the viral genes or viral structural proteins. Convenient that sequenced viral genomes are publicly available in databases. In molecular genetics, gene sequences contain open reading frames (ORFs) that encode regulatory  regions that can potentially be translated into proteins. An ORF is a continuous codon stretch with a start  codon and stops  codon . The phyCoronaviruses are large positive-chain enveloped single-stranded RNA viruses, and the 5′-terminal has two open reading frames (ORFs), 1a and 1b, and encodes two large polyproteins that are processed by viral proteases and involved in viral RNA synthesis –210. TheHIV and other retroviruses are also RNA viruses and have three main open reading frames (ORFs). First, a gag or group-specific antigen is the major structural protein. The second ORF is pol, encoding a polyprotein containing reverse transcriptase, integrase, and protease precursors. The third–env–encodes glycoproteins that are displayed on the virus's surface and cause viral recognition and fusion with the host cell . Corti eInfluenza A, B, and C are negative-sense, single-stranded, segmented, and enveloped RNA  viruses that belong to the orthomyxoviridae family. The influenza virus genome contains 7–8 single-stranded RNA gene segments  that encode ten different proteins. Matrix protein (MP), hemagglutinin (HA), neuraminidase (NA) proteins are present on the influenza virus surface and play essential roles in infecting a host cell. Hemagglutinin protein (HA) and neuraminidase protein (NA) are grouped into subtypes 16 and 9, and the sequences of these subtypes are very different even in subspecies, making them an effective means of monitoring viral changes. The influenza virus is unique due to mutations that lead to changes in two external proteins, HA and NA. Currently, antibodies to the NP gene are the sequence of the target molecule to detect influenza. Hemagglutinin (HA) gene and neuraminidase (NA) gene sequences are the most critical antigenic sites for producing a protective immune response. Matrix protein (MP) genes for influenza A and B viruses, hemagglutinin (HA) gene sequences for influenza C virus were used as targets for PCR primers as well as other nucleic acid amplification methods in 1991 . A compaBy Starick et al., the influenza A virus RNA was purified/prepared by the acid guanidine-thiocyanate method , hemagglSpackman et al. were developed a real-time RT-PCR assay based on matrix protein (MP) gene sequence as target primer . The autLoop-mediated isothermal amplification method (LAMP) —for DNR gag and pol regions of the genome [NASBA—self-sustained and repetitive sequence replication and transcription reactions are very similar to PCR or real-time PCR techniques because of oligonucleotide primers. A multilevel and complex isothermal method is suitable for detecting RNA viruses: HIV –243, core genome –250 is 9All the nucleic acid amplification methods listed here are widely used for detecting different viruses in samples. However, they are also commonly used in the application by combining other regions of the genome sequences to see individual virus prototypes  to increA slight improvement in RT-PCR allowed the discovery of the Abbott ID Now COVID-19 method. The Abbott ID Now molecular point-of-care COVID-19 detection test is associated with high sensitivity and specificity, providing reliable positive results in 5–13 min , 253. AbConventional virologic methods are well known established . The culThe hemagglutination inhibition (HAI)  method tDirecting is an enzyme-linked immunoassay (EIA) membrane method performed in a solid membrane based on an enzymatic reaction between enzyme-conjugated monoclonal antibodies specific towards virus proteins. Then the captured virus antigen–antibody pair is visualized by an enzymatic color development reaction , 266. ThIn the case of COVID-19 after 14 days , direct In the case of HIV, another assay for virions, the enzyme-linked immunosorbent assay (ELISA) detecting HIV-1 gag, p24, has low sensitivity (103 to 106 virus particles/ml) and can also detect virus-like particles lacking genomic RNA and p24 released from dead cells –276.For the semi-quantification of immunoglobulin G (IgG) antibodies in human serum, the lateral flow point-of-care techniques with specially designed recombinant viral proteins are increasingly started to use. The point-of-care system combines a biotinylated aptamer with a streptavidin test line and a secondary antibody control line. Rapid antibody tests are available, but the method cannot use them to monitor viral progression. Recent works with the Ebola virus , influenEnzyme-linked immunosorbent assay (ELISA)  techniqugp120 and gp160 [p65, p51, gp41, p35, p24, p18) are detected in saliva at random without a clear correlation [3O4 and nanocluster (FNC) modified with a silica coating were chosen as the capture probe to inhibit the activity of enzymes from the iron oxide surface (Mag). The fixation probe recognizes the target virus by a specific antigen–antibody interaction, after which the antibody-antigen structures are assembled while applying a magnetic field. Specific antigen–antibody or receptor-ligand interaction can be determined by various physicochemical methods ranging from micromechanical [Conservative sequences of the viral envelope genome are constructed for the ELISA method, which aims to detect antibodies to the virus formed in the body. Antibodies to the HIV envelope proteins nd gp160  are the relation  with therelation –293. Sturelation . The mearelation , 296. ELrelation –303 authchanical , gravimechanical , 306, opchanical , 308, suchanical –311, ellchanical –314.Electrochemical sensors sometimes are less sensitive in comparison to some other analytical signal detection methods mentioned above. However, they enable the determination of antibodies against some virus-proteins or vice versa—virus-proteins in somewhat turbid samples –314 so tSpecific High-sensitivity Enzymatic Reporter un-LOCKing (SHERLOCK) and DNA Endonuclease Targeted CRISPR Trans Reporter (DETECTR) are diagnostic tools that are based on the CRISPR-Cas system and can be used to detect specific RNA or DNA at low attomolar concentrations . CRISPR Gootenberg et al. 2018 developed a method for a multiplexed and portable nucleic acid detection platform –345. SHE4–105 copies/ml [To detect the SARS-CoV-2 virus, the guide RNA is constructing according to the conservative sequence of the neuraminidase (N) gene, spike (S) gene, and replicase polyprotein 1ab (Orf1ab) gene , 353 undopies/ml , 356 senopies/ml  and have4 copies/ml sensitivity is achieved. Primers targeting the SARS-CoV-2 genes E (envelope) and N (nucleoproteins) were designed [Chen et al. reported  the DETEdesigned  for the designed . Detectidesigned .Nucleic acid amplification assays are described as a ‘Gold Standard’ method because of the general-purpose reagents manufactured and approved according to International Organization for Standardization (ISO) normative compliance and quality assurance (QA) rules for the accuracy of the method. Therefore, the regulatory framework and the validity of the technique ensures the reproducibility of the results, and the method is still widely used in the study, research, investigation, and detection of viruses and other pathogens. However, the new generation analytical method based on the nonspecific DNA cleavage observed in CRISPR-Cas type II (Cas9), V (Cas12 and Cas14), and VI (Cas13) systems provide promising advances in CRISPR-based diagnostics of emerging infectious diseases. Already developed and commercialized SHERLOCK and DETECTR methods are straightforward to apply for the detection of new pathogens. However, separate parts of the diagnostic procedure  as in nucleic acid amplification assays are necessary, and a more significant signal is obtained by more straightforward extraction of RNA from body fluid directly. These two advanced methods are based on thorough validations and field tests of diagnostic techniques to guarantee their functionality and ensure that virus or other pathogens detection is susceptible, high quality, specific, and well-functioning. Besides, the sensitivity and accuracy of the methods depend only on the chosen virus ORF gene sequence region. Hence it is worth picking several specific sequences in ORF-region for multiplex assay to quickly and accurately diagnose viral infection. However, the diagnosis of viral infections still faces many obstacles. Therefore, the knowledge and clarity about the methods will facilitate progress in this area.


Begomovirus, family Geminiviridae) with ssDNA genomes infecting sweet potato and other species of the family Convolvulaceae. Deltasatellites  are small-size non-coding DNA satellites associated with begomoviruses. In this study, the genetic diversity of deltasatellites associated with sweepoviruses infecting Ipomoea indica plants was analyzed by further sampling the populations where the deltasatellite sweet potato leaf curl deltasatellite 1 (SPLCD1) was initially found, expanding the search to other geographical areas in southern continental Spain and the Canary Islands. The sweepoviruses present in the samples coinfected with deltasatellites were also fully characterized by sequencing in order to define the range of viruses that could act as helper viruses in nature. Additionally, experiments were performed to assess the ability of a number of geminivirids  to transreplicate SPLCD1 in their natural plant hosts or the experimental host Nicotiana benthamiana. The results show that SPLCD1 can be transreplicated by all the geminivirids assayed in N. benthamiana and by tomato leaf curl New Delhi virus in zucchini. The presence of SPLCD1 did not affect the symptomatology caused by the helper viruses, and its effect on viral DNA accumulation depended on the helper virus–host plant combination.Sweepoviruses are begomoviruses (genus  Begomovirus, family Geminiviridae) have circular, single-stranded DNA (ssDNA) genomes composed of one or two genomic components. They are encapsidated in twinned quasi-icosahedral (geminate) particles )I. indica sample (MW574045 and MW587238). A chimera also containing sweepovirus and deltasatellite sequences was found previously in a sweet potato plant sampled in the Canary Islands [I. indica, and other ornamental species of the genus Ipomoea. This favors virus accumulation and perpetuation, mixed infections, and occurrence of recombination [What has been identified in this work is a recombination event that must have led to the formation of a deltasatellite-sweepovirus chimera with the typical size of a deltasatellite. The putative parentals involved in the generation of this chimeric molecule by recombination were isolates of SPLCV and SPLCD1 closely related to isolates present in the same  Islands . This ch Islands ,47. Vegebination . This phbination ,49,50). I. indica samples.Phylogenetic analysis of a number of deltasatellites associated with NW begomoviruses in Cuba  or sweepN. benthamiana as a plant host, the helper virus range was successfully extended to a bipartite OW begomovirus, ToLCNDV; a bipartite NW begomovirus, SiGYVV; a monopartite NW begomovirus, ToLDeV; and a curtovirus, BCTV. These compelling results indicate that SPLCD1 has a broad range of helper viruses including members of all major groups of begomoviruses and extending to members of a different virus genus in the family, the genus Curtovirus. This helper virus range is wider than that of other deltasatellites for which this has been studied in N. benthamiana: Sida golden yellow vein deltasatellite 1 (SiGYVD1) and tomato yellow leaf distortion deltasatellite 2 (ToYLDD2), deltasatellites naturally associated with bipartite NW begomoviruses. SiGYVD1 and ToYLDD2 were maintained by the monopartite NW begomovirus ToLDeV, in addition to their respective natural helper begomoviruses, but not by the monopartite OW begomoviruses ACMV, TYLCV, and TYLCSV or the curtovirus BCTV [Datura stramonium plants by TYLCV, the bipartite OW begomovirus African cassava mosaic virus, and BCTV [In order to deepen the understanding of the role that deltasatellites may have on begomovirus diseases and epidemiology, the helper virus range of SPLCD1 was studied experimentally. Previous to this work, the experimental helper virus range of SPLCD1, in addition to SPLCV, was limited to two monopartite OW begomoviruses, TYLCV and TYLCSV . In thisrus BCTV . On the and BCTV . There iIn this work, the transreplication of SPLCD1 by ToLCNDV, SiGYVV, ToLDeV, and BCTV was also assessed in their natural host plants. The only positive result was obtained with ToLCNDV in zucchini, with about half of the virus-infected plants also infected by the deltasatellite. The fact that SPLCD1 can be transreplicated by ToLCNDV in zucchini may have significant epidemiological importance. This virus has a wide host range, infecting more than 40 plant species , and altN. benthamiana plants , the begomovirus accumulation decreased in the presence of the deltasatellite [I. setosa, SPLCD/TYLCV/tomato, SiGYVD1/SiGYVV/M. coromandelianum, and ToYLDD2/ToYLDV/Sidastrum micranthum [N. benthamiana, no effect of the deltasatellite on viral accumulation was observed either [N. benthamiana, the presence of the deltasatellite decreased the begomovirus accumulation as it has been shown for most of the abovementioned cases. On the contrary, accumulation of the curtovirus BCTV was not affected by the presence of the deltasatellite.Previous to this work, the influence of deltasatellites on helper virus accumulation had not been thoroughly addressed, with only a few analyses done by quantifying densitometry of Southern blots for a number of deltasatellite/begomovirus combinations. Summarizing, in most of the deltasatellite/begomovirus combinations agroinoculated in atellite ,34. In ccranthum ,34. In tN. benthamiana plants. On the other hand, this effect was not observed in zucchini plants, a natural host for the cucurbit-adapted ToLCNDV isolate used in this study [A particular and interesting case is the response of ToLCNDV to the presence of SPLCD1. This is the first time that a deltasatellite has been shown to increase the accumulation of a helper geminivirid, in this case in is study , where SEuphorbia heterophylla and N. benthamiana [Arabidopsis thaliana. For EuYMV DNA-B, no differences in its accumulation are observed in the presence or absence of EuYMA in both N. benthamiana and A. thaliana, but results in E. heterophylla show an increase of EuYMV DNA-B accumulation in the presence of EuYMA [The contrasting effect of deltasatellites on helper virus accumulation depending on the virus–host combinations found in this study and in previous research ,34, exemthamiana . Howeverof EuYMA .N. benthamiana or tomato [In most cases where a possible effect of deltasatellites on the symptomatology caused by the helper geminivirid has been assessed, no symptom modifications have been observed, despite the effect on virus accumulation that was observed for some of the deltasatellite/virus combinations ,34,41. Tr tomato . In thisIn nature, known deltasatellites seem to have a narrow helper virus range because closely related isolates of a single begomovirus species have been reported per deltasatellite species ,23,34,41A narrow helper virus range of deltasatellites in turn would restrict the plant host range that deltasatellites could potentially infect. However, the promiscuous replicative nature of deltasatellites that is being revealed in this and other studies ,34,41, cAlthough deltasatellites and betasatellites are clearly related , there a


Culicoides midges and affected ruminants during June 2018–December 2019, demonstrating its circulation in Israel. This region is a geographic bridge between 3 continents and may serve as an epidemiologic bridge for potential Schmallenberg virus spread into Asia.We discuss genomic detection of Schmallenberg virus in both  Orthobunyavirus of the family Peribunyaviridae, comprising >25 antigenically different, but serologically related, negative-sense single-stranded RNA viruses. These viruses are transmitted mainly by Culicoides biting midges; they persist in the environment by cycling between infected mammalian hosts and Culicoides vectors. Notable examples from the Simbu serogroup are Akabane virus (AKAV), Aino virus, Schmallenberg virus (SBV), Sathuperi virus (SATV), Shamonda virus (SHAV), Peaton virus (PEAV), and Shuni virus . These viruses are known to cross the placenta of ruminants to the developing fetus, causing abortion, stillbirth, and neonatal malformations that are seen only at birth. The congenital malformations are termed arthrogryposis-hydranencephaly syndrome. Given that the clinical signs can be observed only months after viremia has occurred, field and laboratory practitioners are at a huge disadvantage when facing epidemics caused by these viruses  around livestock farms, and we tested CSF from 3 malformed 1-day-old lambs  and 1 malformed 11-day-old calf   according to the manufacturer’s instructions. We used total viral nucleic acids (0.4 µg) for cDNA synthesis by UltraScript Reverse transcription  according to the manufacturer’s instructions. We performed reverse transcription (RT) nested qPCR targeting the L RNA segment of Simbu serogroup viruses according to Behar et al.  (Of the 31 species-specific pools from the 4 Culicoides pools collected from several of those farms (In general, the most susceptible period for induction of congenital malformations by Simbu serogroup viruses is 65–70 days of gestation in lambs and 150 days of gestation in calves . The detOur results demonstrate the circulation of SBV outside Europe. Future studies are needed to determine the seroprevalence of SBV in the Middle East, because this information is essential for understanding the risk of SBV spread into countries in Asia. Because SATV is found in the Middle East (Additional information on the genomic detection of Schmallenberg virus, Israel.


Mosquitoes not only transmit human and veterinary pathogens called arboviruses (arthropod-borne viruses) but also harbor mosquito-associated insect-specific viruses (mosquito viruses) that cannot infect vertebrates. In the past, studies investigating mosquito viruses mainly focused on highly pathogenic interactions that were easier to detect than those without visible symptoms. However, the recent advances in viral metagenomics have highlighted the abundance and diversity of viruses which do not generate mass mortality in host populations. Over the last decade, this has facilitated the rapid growth of virus discovery in mosquitoes. The circumstances around the discovery of mosquito viruses greatly affected how they have been studied so far. While earlier research mainly focused on the pathogenesis caused by DNA and some double-stranded RNA viruses during larval stages, more recently discovered single-stranded RNA mosquito viruses were heavily studied for their putative interference with arboviruses in female adults. Thus, many aspects of mosquito virus interactions with their hosts and host-microbiota are still unknown. In this context, considering mosquito viruses as endosymbionts can help to identify novel research areas, in particular in relation to their long-term interactions with their hosts  and the possible context-dependent range of interactions . Here, we review the symbiotic interactions of mosquito viruses considering different aspects of their ecology, such as transmission, host specificity, host immune system and interactions with other symbionts within the host cellular arena. Finally, we highlight related research gaps in mosquito virus research. For instance, DNA viruses from ectively . Followiectively . In partectively . Notablyectively  and are ectively , suggestGiven their intimate and long-term associations with their hosts, we argue that both RNA and DNA mosquito viruses should be studied as mosquito endosymbionts. To date, mosquito virus studies have mostly been focused on i) virus discovery, ii) larval biocontrol or iii) interactions with arboviruses. As the viruses are too often seen as pathogens transiently introduced into a symbiotic system (the mosquitoes and their microbiota), mosquito viruses’ long-term association with their hosts and range of their interactions  are understudied. Thus, investigating mosquito viruses as endosymbionts can improve our understanding of their long-term associations, as well as the wide range of interactions with their hosts and hosts’ microbiota. For instance, several mosquito viruses persistently infect mosquitoes through larval and adult life stages, although whether the infection is actively maintained or merely tolerated by the host immune system is unknown. Similarly, several mosquito viruses can be transmitted vertically, although whether they are fixed in populations or stable on evolutionary timescales is not well investigated. Like other endosymbionts, the interactions between mosquito viruses and their hosts can be diverse, and the outcomes of these interactions may be context-dependent, as shown for a plant virus that confers drought tolerance to its hosts when evolved in drought conditions .Here, we review current knowledge of the interactions between mosquito viruses and their hosts and other symbionts sharing the same cellular arena. The factors  that influence the outcome of these interactions are presented ((Parvoviridae) known for their high pathogenicity  decreased naturally infected Cx pipiens mosquitoes’ flight behavior , but negatively with AeDV prevalence in adults, in the following month (Abiotic factors (e.g. temperature or water pH) can influence the outcome of host-virus interactions through their effect on the individual host (e.g. host immunity) or host populations (e.g. population density), or alternatively by altering the infectivity of the virus. The effect of abiotic factors on mosquito virus infections has been mostly studied for dsRNA and DNA viruses of mosquitoes during larval stages, but little to no information is available for RNA viruses. Infectivity of mosquito baculoviruses and reoviruses can depend on ion composition in the rearing water . Temperang month . Thus, iOverall, the nature of mosquito virus interactions with their hosts may be context-dependent and could be influenced by various biological and ecological factors such as transmission routes, host range, and host antiviral immunity  (Flaviviridae) and the Yichang virus can infect larvae when added to rearing water; although this was not the case for CxFV   but was k virus) . Mosquitfor CxFV . Howeverulations .Aedes, Culex or Uratoaenia larvae when added to their habitats  depending on the virus titre in females  and dsRNA (reoviruses) mosquito viruses have focused primarily on horizontal transmission during the larval stages . Indeed,habitats . A vectos larvae . On the  females . Another females . In addi females .Although exclusive vertical or horizontal transmission cannot be excluded, to date, studies suggest that mixed-route transmission, including both horizontal and vertical transmission routes, is likely key to mosquito virus persistence and dispersal in nature. Each transmission route’s role for a given host-virus combination may change depending on the ecological context. Although not explicitly studied for mosquito viruses, abiotic conditions that affect the host population density could also cause a switch between transmission routes, as horizontal transmission may play a greater role in high population density than low population density . FurtherFlaviviridae, Togaviridae and Bunyavirales), host range studies have focused solely on their inability to infect vertebrates . For instance, Aedes aegypti densovirus (AeDV) and Aedes albopictus densovirus , isolated from Ae. aegypti and Ae. albopictus, respectively, can infect Aedes, Culex and Culiseta species but not Anopheles species or other insects tested  infects only An. gambiae but not An. stephensi  in Ae. albopictus and Cx. tarsalis cell lines. However, CPE was not observed in An. albimanus, where the virus replicates successfully  Aedes densovirus  prevalence while all tested Ae. albopictus adults were negative  pathway as it acts antiviral against all investigated arboviruses, to date . RNAi isAll studies, to date, have shown that mosquito virus-derived small RNAs are produced, proving an interaction between the mosquito RNAi response and mosquito viruses (for both DNA and RNA viruses) . It is nBunyavirales, Reoviridae, Rhabdoviridae and Flaviviridae have been found in the genome of a variety of mosquito species. NIRVs in mosquitoes have been linked to the piRNA pathway, as mosquito virus-derived NIRVs were mostly found in piRNA clusters in mosquito genomes and the production of NIRV-specific piRNAs was also shown  reduce the expression of a reporter construct harboring CFAV-specific NIRV target sites or (iii) inhibit the infection of a virus harboring CFAV-specific NIRV target sites. These data support the hypothesis that the acquisition of NIRVs, at least in the mosquito genome, acts as an adaptive immune response. Such integration of mosquito virus sequences can occur in somatic or germ cells, but only the latter can be transmitted vertically to the offspring. Therefore, tissue specificity of mosquito viruses strongly influences vertical NIRV transmission, hence the acquisition and transmission of this “adaptive immune response”. Moreover, a comparison of different mosquito genera, sampled from the same habitats suggests that NIRV integration is not just a mere result of virus exposure but also depends on specific virus-host interactions  related to mosquito viruses have been reported from mosquito genome sequences . EVEs orso shown . Moreoveso shown . In bothractions . The maj aegypti . Until nThere are still many unanswered questions about how this would affect a virus infection in nature, the extent to which this “adaptive” immunity shaped the virus evolution, and the frequency of the functional EVEs derived from mosquito viruses  through the production of a bacterial protein called smEnhancin. Indeed, smEnhancin has been shown to facilitate viral dissemination from the gut by digesting mucines on the mosquito gut epithelia  interferes with West Nile virus  replication but not with Ross River virus (Togaviridae) replication in Aedes-derived mosquito cells (C6/36) (Phenuiviridae) in Cx. pipiens (Flaviviridae) in vitro and reduce its transmission rate in Ae. albopictus (Togaviridae) infection both in vivo and in vitro in An. gambiae  . Culex F (C6/36) , althoug pipiens . So far,bopictus . In cont gambiae .Arboviruses mainly infect female adult mosquitoes through infectious blood meals although they can be transmitted vertically at very low rates . Unlike Wolbachia   was observed in Aedes-derived cell lines transinfected with wMelPop (from Drosophila melanogaster) or wAlbB , compared to control cells  (Flaviviridae) replication was limited by wMelPop, wMel and wAlbB in transinfected Ae. aegypti-derived cell lines   and Aedeviridae) , respectol cells . No inflvirales) . In contll lines . Howeveriviruses .Wolbachia and mosquito viruses were also studied in a natural system, where the native Wolbachia, the host and a mosquito virus have potentially evolved together. Culex pipiens (s.l.) populations that are naturally infected with Wolbachia wPip (wPip can be co-transmitted to the offspring of Cx. pipiens (s.l.) lines vertically. CpDV levels in ovaries and its vertical transmission decreases significantly in wPip free mosquitoes compared to wPip infected females  was associated with higher CpDV loads in ovaries of laboratory colonies (wPip type (i.e. wPip-I) . Thus, it is possible that mosquito viruses associated with the more advantageous wPip strain could also invade the host population if vertically co-transmitted.Interactions between hia wPip  also harhia wPip . In the  females . These rcolonies  and a hi wPip-I) . wPip invia toxin production) or indirectly through their extended phenotype   can be vertically transmitted to their vector’s offspring by binding to the outer membrane protein of Sulcia  with its viral capsid protein  depends on the presence of Hamiltonella bacteria in its whitefly vector (Bemicia tabaci), as the GroEL protein of Hamiltonella binds to the capsid of TYLCV, facilitating the transmission to host plants  . The “facrobiota . Protein protein . Similart plants . Indirece.g. “the” pathogen Vibrio cholerae or “the” mutualist Buchnera aphidicola) like previously thought, but are driven or influenced by interactions between microbial communities in an organism (Extended phenotypes do not solely result from host-symbiont or symbiont-symbiont interactions (organism . This paorganism . Howeverorganism . One wayNasonia (Nasonia bacterial microbiota and virome exhibited a pattern of phylosymbiosis, primarily driven by bacteriophages hosted by the bacterial microbiota (The evolutionary history of a host explaining the divergence of its microbial community is a phenomenon called “phylosymbiosis” . PreviouNasonia . Nasoniacrobiota . Recent crobiota . The potThe discovery of mosquito viruses has increased exponentially over the past decade, and their interactions with arboviruses have attracted much scientific attention. Nevertheless, many questions related to mosquito virus interactions remain unanswered (Mosquito viruses are often overlooked in studies of the mosquito microbiota, yet their symbiotic interactions with their hosts and the rest of the microbiota could define host fitness and vector competence. As has been observed for other symbionts, the nature of these interactions could be context-dependent. They can shape microbial communities and host populations by influencing infection outcomes and can drive the evolution of the different partners involved.Nevertheless, due to their medical importance, mosquitoes are already well studied for many arbovirus-related aspects. Current knowledge could be leveraged to achieve a more holistic understanding of the mosquito and associated microbiome, including viruses, which will also contribute to mosquito and arbovirus control. The study of non-model organisms and their bacterial symbionts has advanced our knowledge of host-symbiont interactions in previous years. Mosquito viruses may do the same in the future and change our understanding of virulence and virus ecology and evolution.MA wrote the first draft of the manuscript and made the figures. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


We aimed to provide reliable regression estimates of expenditures associated with various complications in type 2 diabetics in China. In total, 1,859,039 type 2 diabetes patients with complications were obtained from the Beijing Medical Claim Data for Employees database from 2008 to 2016. We estimated costs for complications using a generalized estimating equation model adjusted for age, sex, and the incidence of various complications. The average total cost for diabetic patients with complications was 17.12 thousand RMB. Prescribed drugs accounted for 63.4% of costs. We observed a significant increase in costs in the first year after the onset of complications. Compared with costs before the incidence of complications, the additional costs per person in the first year and >1 year after the event would be 10,631.16 RMB and 1150.71 RMB for cardiovascular disease, 1017.62 RMB and 653.82 RMB for cerebrovascular disease, and 301.14 RMB and 624.00 RMB for kidney disease, respectively. The estimated coefficients for outpatient visits were relatively lower than those of inpatient visits. Complications in diabetics exert a significant impact on total healthcare costs in the first year of their onset and in subsequent years. Our estimates may assist policymakers in quantifying the economic burden of diabetes complications. Diabetes is a common challenge faced by both developed and developing countries and imposes a heavy burden on national economies and medical systems. According to the International Diabetes Federation, the disease affected 451 million adults worldwide in 2017, and global healthcare costs for diabetics were estimated to be USD 850 billion ,4,5. As As more diabetes treatment options emerge, economic evaluations of the related costs become important. Previous systematic disease models such as those of the Centers for Disease Control and Prevention/RTI International and the UK Prospective Diabetes Study are available to assess the cost-effectiveness of disease intervention programs ,11. ThesTo date, only a few studies have investigated the medical costs of diabetes complications in China, and these studies only analyzed the average cost of a specific complication or a total complication based on a single or several hospitals ,9,13. InThe health data used in this study were extracted from the Beijing Medical Claim Data for Employees (BMCDE) database, which was described previously . All empPatients with type 2 diabetes were identified using the E11 code in ICD-10 and/or prescriptions for hypoglycemic drugs or insulin. Data from 1 January 2008 to 31 December 2016 were included. Diabetic complications consisted primarily of acute complications such as diabetic ketoacidosis and diabetic coma and chronic complications . http://tjj.beijing.gov.cn/, last retrieved on 27 February 2021).Chinese currency experienced sustained inflation between 2008 and 2016. To better reflect the real monetary value, all costs were expressed in 2008 China Yuan (RMB) by dividing a monetary time series of the consumer price index in Beijing . Annual To ensure the reliability of the statistical analysis, each step was double-analyzed. We also checked the quality and plausibility of the data, removing outliers such as negative medical costs . We usedp < 0.05 was considered statistically significant. Statistical analyses were performed using SAS version 9.4 .We used descriptive analyses for demographic and complication characteristics of type 2 diabetic patients. The consumer price index-adjusted average total medical costs were calculated by year and type of complication. Categorical variables were expressed as percentages. We used a generalized estimating equations (GEE) model with a Gaussian distribution to explain the nonindependence of observations within each subject during the study period  [p < 0.001) [Our findings of rising costs after the onset of complications were consistent with those of previous studies. A cross-sectional study in rural southeast China reported that the mean total cost for patients with one complication was USD 1399, and the total hospitalization and outpatient costs of patients with complications were 83.55% and 38.46% higher, respectively, than those of patients without complications . A study< 0.001) . Similar< 0.001) ,12. Furt< 0.001) ,21,22.Our subgroup analyses indicated that the cost of complications was higher in men, but perhaps this difference may have been related to age distribution, as the men in our study were, on average, 2.8 years older than the women. Moreover, some diseases displayed sex-based differences in severity and subtype distribution ,24,25. TWe also compared outpatient and inpatient costs using the GEE model. The cost of most complications increased significantly after the initial diagnosis of the disease. It is important to note that a significant increase in outpatient costs was only observed one year after the initial diagnosis of the complication; perhaps the symptoms are more severe in the first year of diagnosis, leading to more hospitalization ,31. AfteOur study has several strengths. First, we used regression analysis to reliably estimate the costs associated with various complications in type 2 diabetics, adjusting for sex, age, and other complications. Second, this study is based on medical insurance data from Beijing, providing a large and representative sample of the costs of diabetes and ensuring the stability of the results. The large sample also enabled us to assess some less-prevalent complications such as diabetic ketoacidosis and diabetic coma. Third, we included patients who had been insured throughout the study period and had annual medical records, maintaining the integrity of cost-tracking. However, some potential limitations should be noted. First, the data in this study are from the BMCDE database, which does not include individuals under 18 years or temporary or seasonal residents. Thus, the study did not cover all of Beijing’s population, and we were unable to analyze the related costs for children. Second, as in previous studies using the large administrative health database, we could not fully explore other related covariates like BMI, glucose level, smoking, and functional status, which are considered to be associated with healthcare costs. Future studies are needed to investigate the effect of these covariates on costs of complications. Third, we only know the initial diagnosis time of the complications rather than the true onset time, which should be evaluated by prospective clinical studies.In conclusion, complications in type 2 diabetics had a significant impact on total medical costs, especially in the first year of the events. Male patients, the elderly (>75 years old), and patients who required hospitalization were the groups with the highest medical costs. Our study provides new evidence for investigating diabetes costs and may promote future research in the field of diabetes modeling in China.


Mosquito-borne Zika virus (ZIKV) was considered an obscure virus causing only mild or self-limited symptoms until the explosive outbreaks in French Polynesia in 2013–2014 and in the Americas in 2015–2016, resulting in more than 700,000 cases of the disease, with occasional miscarriage and severe congenital birth defects, such as intrauterine growth restriction, fetal microcephaly, and other neurodevelopmental malformations. In this review, we summarized the evolution of ZIKV from a mundane virus to an epidemic virus. ZIKV has acquired a panel of amino acid substitutions during evolution when the virus spread from Africa, Asia, Pacific, through to the Americas. Robust occurrence of mutations in the evolution of ZIKV has increased its epidemic potential. Here we discussed the contributions of these evolutionary mutations to the enhancement of viral pathogenicity and host-mosquito transmission. We further explored the potential hypotheses for the increase in ZIKV activity in recent decades. Through this review, we also explored the hypotheses for the occurrence of the recent ZIKV epidemics and highlighted the potential roles of various factors including pathogen-, host-, vector-related, and environmental factors, which may have synergistically contributed to the ZIKV epidemics. Flavivirus together with other important mosquito-borne human viruses, such as dengue virus (DENV), West Nile virus, Japanese encephalitis virus, and yellow fever virus. The flaviviruses have single positive-stranded 11-kb RNA genomes that the 5’ and 3’ untranslated regions flank a polyprotein coding region encoding three structural proteins  and seven non-structural proteins . The main mosquito vector during epidemics belongs to the genus Aedes   belongs to the genus opictus) . ZIKV han saliva , urine  cells, human neuronal progenitor cells (NPCs) as well as neuroblastoma, glioblastoma, and monocyte-derived dendritic cells  strain and different contemporary Asian strains isolated after 2010 . One stu in vivo . The autsquitoes . Taken tA. aegypti mosquitoes and elevated NS1 antigenemia without altering infective virus propagation in AG6 mice   ; howevernt (ADE) . In the nt (ADE) . One epint (ADE) . In murihallenge . Heterothallenge . NonetheAedes spp. mosquito range correlates with an increase in water storage during regional periods of drought (Aedes spp. expansion, a model was recently developed and applied to predict the time required for each A. aegypti life cycle based on the biophysical response to environment conditions (A. aegypti from 1950 to 2000 and will accelerate to 3.2–4.4% by 2050, emphasizing the recent gradual expansion of A. aegypti. These studies simultaneously indicate that global climate change, including temperature elevation, potentially increase the Aedes spp. development and expansion. Hence, all three major components, namely, pathogen, host, and environment, likely contribute to the observed increase in ZIKV prevalence and, as such, must each be taken into account when considering the recent ZIKV emergence.The environment accounts for the third major component in the epidemiologic triad . The 201 drought . Accordinditions . ResultsWe believe that multiple components have likely synergistically contributed to the debilitating ZIKV outbreaks observed in recent years. Although the number of ZIKV cases reported globally has declined since 2017, surveillance data shows that ZIKV continues to be detected in several areas and in travelers from endemic regions. In future, global surveillance, differential diagnosis, vector control, and virus sequencing are required for prompt monitoring of the transmission dynamics and providing early warnings of possible ZIKV outbreaks in future. Moreover, ZIKV vaccine development is urgently needed to control the next wave of a potential outbreak; however, preexisting flavivirus antibodies in people with prior flavivirus infection or vaccination call for great caution in the design and implementation of vaccines.S-WH and S-JH: conceptualization, data curation, writing – original draft, and writing – review and editing. S-WH: project administration, resources, supervision, and visualization. Both authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.