Gossypium spp. L., Malvaceae) is the world’s largest source of natural fibers. Virus outbreaks are fast and economically devasting regarding cotton. Identifying new viruses is challenging as virus symptoms usually mimic nutrient deficiency, insect damage, and auxin herbicide injury. Traditional viral identification methods are costly and time-consuming. Developing new resistant cotton lines to face viral threats has been slow until the recent use of molecular virology, genomics, new breeding techniques (NBT), remote sensing, and artificial intelligence (AI). This perspective article demonstrates rapid, sensitive, and cheap technologies to identify viral diseases and propose their use for virus resistance breeding.Cotton ( Gossypium spp. L.  is the largest source of natural fibers in the world. The widely cultivated cotton cultivars are allotetraploid species. More than 90% of the annual cotton crop worldwide is Gossypium hirsutum (AD1), Upland or American cotton, and less than 10% is Gossypium barbadense (AD2), extra-long-staple, or Pima cotton , digital disease assessment and phenotyping (DDAP), artificial intelligence (AI), and biotechnological tools may accelerate and enhance the breeding of virus-resistant cotton and help sustain the cotton industry.Solemoviridae , a positive sense (+) ssRNA virus, causes the Cotton Blue Disease (CBD) that affects cotton crops in South America and Africa , one of the most polyphagous aphid species and worldwide-distributed, hosts over 40 viruses , a “cryptic species complex,” which is one of the most agriculturally important pests worldwide  or cotton leaf curl Kokhran virus (CLCuKoV), with the cotton leaf curl Multan betasatellite  as B. tabaci is present in their territories.The 1992–1993 CLCuD epidemic in Pakistan caused economic losses calculated in one billion US dollars  and is aBegomovirus that mimics nutrition deficiency, is hard to diagnose, and proliferates through the Brazillian cotton belt in the Midwest and Northeast regions  and cotton leaf curl Gezira virus associated with cotton leaf curl Gezira betasatellite and cotton leaf curl Gezira alphasatellite, and African cotton mosaic disease virus is spreading at a quick rate from Western to Central Africa and Indo-Pak subcontinent .The cotton bunchy top (CBT), a polerovirus from the Oceania continent, is cotton’s most viral severe disease in Australia. CBT often occurs in patches or on crop edges and is associated with the highest aphid activity areas .Ilavirus, family Bromoviridae), transmitted by thrips, was reported to infect cotton in specific regions of India and Pakistan  transmitted by aphids are coinfecting cotton plants  are the safest way to confirm a virus species and/or strain and a resistant cotton line. After confirming viral resistance, breeders can plan the crosses and breeding schemes. Moreover, molecular and discovery breeders can initiate molecular marker discovery for resistant genes and molecular breeding strategies with the knowledge of contrasting resistant and susceptible cotton lines.Nowadays, molecular virus detecting techniques, such as high-throughput sequencing (HTS), allow the detection of all viruses present in a plant (virome), including undescribed new viruses . HoweverVirome information is essential for breeding and molecular breeding schemes to understand the availability and type of viral-resistant genes needed for elite line introgression. Developing a new resistant elite variety can be fast if a known virus causes the symptoms and resistant germplasm and molecular markers are available. When dealing with a new virus or coinfection, developing a new resistant elite variety will demand germplasm and gene prospection, resources, and time.After completing the virus sequencing step, it is possible to develop new sensitive virus detection techniques and replace costly qRT-PCR-based diagnosis testing systems . Some acin situ screening of human viruses using paper strips. The development of such POCT tools for plant viruses will enable a large-scale, fast, and robust detection of virus on-site, aiding in selecting virus-resistant cotton lines without waiting for symptoms.Among CRISPR-NAT tools, CAS9 has shown to be an ultrasensitive pathogen detection method. Converting the developing NAT to point-of-care testing (POCT) will drastically reduce costs and accelerate viral identification due to on-site identification and easy handling . CRISPR/MVDT are so fast and sensitive that CLRDV is detectable in susceptible cotton plants 24 h after inoculation and 2–5 days in systemic leaves after aphid infection, respectively . MVDT coi) and selection accuracy (r), parameters of the “breeder’s equation” Several available technologies permit digital disease assessment and phenotyping (DDAP) and may reduce operational time, costs, breeding score subjectivity, and increases the genetic gain (ΔG) by increasing selection intensity  and lower reflectance values in the red region  can detect viral diseases with decreased dependence on weather conditions . Swarm r2 of data and can capture healthy vegetation’s spectral signature and anomalies caused by viruses , labeling training data, and high processing time, Deep Learning (DL) enables an automatic and hierarchical learning process . DL has Pathogen-resistant cotton lines appear to have relatively low yields, low fiber quality, and high linkage drag, complicating the development of elite resistant varieties. Implementing integrated cotton molecular breeding strategies , such asMoreover, new breeding techniques (NBT) may be the quickest path to developing elite resistant varieties without the worries of linkage drag . Among tAV2) and antisense coat protein (ACP) genes of CLCuV provide resistance to CLCuD  plants expressing the antisense movement protein  project E-26/010.001716/2019.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.


Cooperation is essential for all domains of life. Yet, ironically, it is intrinsically vulnerable to exploitation by cheats. Hence, an explanatory necessity spurs many evolutionary biologists to search for mechanisms that could support cooperation. In general, cooperation can emerge and be maintained when cooperators are sufficiently interacting with themselves. This communication provides a kind of assortment and reciprocity. The most crucial and common mechanisms to achieve that task are kin selection, spatial structure, and enforcement (punishment). Here, we used agent-based simulation models to investigate these pivotal mechanisms against conditional defector strategies. We concluded that the latter could easily violate the former and take over the population. This surprising outcome may urge us to rethink the evolution of cooperation, as it illustrates that maintaining cooperation may be more difficult than previously thought. Moreover, empirical applications may support these theoretical findings, such as invading the cooperator population of pathogens by genetically engineered conditional defectors, which could be a potential therapy for many incurable diseases. Since then, many partial mechanisms have been suggested, such as kin selection, group selection, reciprocity, policing, spatial structure, sanction, reward, and punishment4. Darwin himself suggested some core concepts of these mechanisms. This paper introduced conditional defector strategies that violate the kin selection, punishment, and spatial structure mechanisms.A long-standing puzzle in evolution theory is how cooperative behavior can evolve and persist within the selfish natural world. Once cooperation exists, it is always prone to exploitation by defective free riders who adopt selfish strategies for reaping the highest possible profit without paying the share. Thus, they invest most of their energy in reproduction. Therefore, cheaters could outcompete the cooperators and take over the population. Haldane pointed out that there was no general principle to solve this problemFrom a conceptual viewpoint, a conditional defector strategy may be any cheating strategy that could somehow cooperate. In other words, it is a cheater who pays additional costs or wastes a portion of the profit to survive. Therefore, it is not necessarily defective in all behaviors or at all times. However, it may cooperate in some behaviors now and then. Consequently, they are not pure defectors.5. Hence, an intermediate dispersal rate of cooperators is essential for cooperation maintenance7. Furthermore, migration can induce an explosive outbreak of cooperation, even in a world of selfish individuals with various sources of randomness, starting with defectors only8. Recently9 showed for the first time that strategy-neutral migration triggered strategy oscillation in a two-strategy game even without the bridging of any transition strategies (states), thus defining a novel oscillating behavior fundamentally different from the conventional cyclic dominance previously found in a game of at least three or more strategies. Reference10 studied the impact of varying migration preferences in promoting cooperation. They revealed the role of orientation-driven migration, where individuals prefer to move closer to their neighboring cooperators or favor escape away from their neighboring defectors.Dispersal is beneficial because it decreases Kin competition, sustains resources, and outsets colonization. Without dispersal, the fate of all populations is extinction12. Therefore, some studies have focused on the joint evolution of dispersal and cooperation13. Alternatively, there is a correlation between cooperation, dispersal rate, and dispersal cost14. Their findings asserted that the low dispersal cost selects against cooperation. Thus, if cheaters reduce their dispersal costs, they may turn the game against cooperators.Nevertheless, dispersal is a costly behavior that increases the mortality of dispersers or decreases their fecundityUsually, cheats are not good migrators because dispersal itself is a cooperative behavior. The migrators leave their suitable habitats to other unknown environments and face dangerous predators to colonize a new patch. Therefore, such behavior is costly for migrators. Nevertheless, its benefits are also gained by non-migrators because it decreases kin competition. Thus, dispersal is considered a cooperative behavior that naturally does not expect to be abundant in cheats. Hence, cheaters go extinct rapidly with the depletion of local patches they dominated without global prevalence like cooperators; this might be the fundamental problem of cheaters. However, the probable solution is adopting a conditional defection strategy wherein free riders would cooperate only for the spread. The actors of this selfish strategy would have a high dispersal rate with the lowest possible cost because they share migration costs. Thus, the exploitation rate of public goods and interactions among defectors and cooperators will increase. In other words, the conditional defectors can exclusively cooperate in all collective behaviors related to migration  but defect otherwise. Therefore, these selfish successful migrators can convert the structured meta-population into a well-mixed game and violate the spatial structure mechanism.15, is considered empirical evidence to assume that individuals reduce their dispersal costs by sharing it. Thereby, they can achieve successful migrations. Additionally, in metastatic cancer, migrating in groups  raises the efficacy to 50-fold more than individual dispersal17.In factConditional defectors can pay some of their wealth or waste some profits to escape punishment by producing substances to mislead punishers. Or possession of the significant tag that marks cooperators. Similarly, by reducing their payoff to be more similar and familiar to cooperators. If cheaters reduced the benefits, it might be hard to have been noticed by a quorum-sensing system or other defense mechanisms. It is considered a kind of imitation or tag-based decision that prevents cooperators from detecting and punishing defectors.Those cheaters pay a cost to escape sanctions or reduce the accuracy of the monitoring/punishment system. Therefore, they can merge with cooperator populations accordingly, violating punishment and kin-selection mechanisms.net logo models created by Dr. Susan Hanisch.We used two agent-based simulation models to investigate the concepts of "cooperate for the spread" and "pay for the escape," both were Afterward, we modified the first model to represent the concept of sharing the dispersal costs. We used the second model without modifications. Instead, we assigned definite values of some parameters that highlight the pay for the escape strategy.18. She first developed it for educational purposes. It illustrates the concepts of cooperator-cheater competition, natural selection, spatial structure mechanisms, multilevel selection, and founder effects.The original model was entitled "Evolution and patchy resource"Distance-resource-areas: the distance between the centers of the resource areas.Size-resource areas: the size of resource areas as a radius in the number of patches.Living costs: the costs that each agent has to deduct from energy per iteration for basic survival.Mutation rate: The probability that offspring agents have different traits than their parents.Evolution: the ability of agents to produce offspring.The number of patches is 112 × 112 patches.Carrying capacity per patch: Resource = 10, Agents = 1The growth rate of the resource = 0.2The resources on a patch regrow by a logistic growth function up to the carrying capacity: New resource level = current resource level + (Growth-Rate × current resource level) × (1 - (Current resource level/carrying capacity)).The cost for producing offspring is ten subtracted units of energy.The initial level of energy of agents is set at living costs.Agents are distributed randomly in resource areas at the beginning of a simulation.Sustainable behavior is distributed randomly with a probability of percent sustainables among the initial agent population.The order in which agents move and harvest within one iteration is random.Agents move to a randomly selected patch if several patches fulfill the objectives.The order in which agents produce offspring within one iteration is random.Agents reproduce offspring with a probability of (0.0005 × Energy).Agents place offspring on a randomly selected unoccupied neighboring patch.Offspring mutate with a potential mutation rate.If there are no unoccupied patches in a two-patch radius, they stay on the current patch.If there are unoccupied patches with resources amounting to more than living costs, the agents move to them.If the resource amount is less than the living costs, the agents move randomly to other unoccupied patches.In each iteration, each agent moves around in random order. There are three likelihoods:The agents harvest the resources from separated patches to gain energy for metabolism and proliferation. If the energy level of any agent falls to zero, it dies. The cooperator type harvests half of the resource, while the greedy type consumes 99%.The living costs are deducted from the energy amount of the agent constantly everywhere all the time. This process occurs whether an agent moves within the patch, between the patches, or even not. Therefore, the model does not consider dispersal cost explicitly.If there is an unoccupied neighbor patch, the agent can reproduce with a probability of 0.0005 of his energy, place the offspring on the unoccupied neighbor patch, and then transfer ten units of the energy to his offspring.Resources regrow only on resource patches. When the resource amount is more than or equal to 0.1, then it regrows. When the resource is less than 0.1, its value is set to 0.1.The average energy of agents: average energy levels of sustainable and greedy agents, resulting from resource harvest minus living costs and reproduction.Trait frequencies: the relative frequencies of sustainable and greedy agents in the total population, resulting from mutations, different reproduction rates, and death.Agent population: the absolute number of the total population size resulting from reproduction and death.In the first modification, we added a different type of cost that agents only incur when they disperse from one patch to another (in-between the patches). It is the slider entitled "dispersal costs".In the second modification, we added another sharing dispersal costs tool to reduce them by dividing their value by the number of included agents (flock-mates) in the identified range from the same type. It is the slider entitled "group-dispersal-range." which is the flock mate's areas as a radius in the number of patches. Therefore, changing the value of the group dispersal range will change the area around every agent. Accordingly, the number of its flock mates who share the dispersal costs also adjusts.The group dispersal range is not confined to greedy agents but applies to all agents. Therefore, it represents the case of the wild-type cooperators who can also cooperate for the spread. The group dispersal range also does not only target the agents in between patches. However, it counts the agents inside and outside the patches. For example, once an agent starts its dispersion with a determined range containing ten agents, four from another type, three non-dispersal agents from the same type that existed inside a patch, and three dispersal agents from the same type outside the patches. The dispersal costs for this agent will be divided by 6.20 or if they are non-motile21. On the other hand, dispersion is an extended process with many factors, including escape from predators, suppression of host defense mechanisms, and production of biosurfactants to reduce surface tension to facilitate motility. Therefore, the agent's contribution (inside/outside the patches) to support such factors is considered a shared dispersal cost.Our assumption that non-dispersal agents at the pre-departure stage share dispersion costs with dispersal agents; seems justified because they reap mutual benefits by reducing kin competition inside patches if they promote the migrators. However, can agents remotely pay the dispersion costs? Yes. For instance, some bacterial species can trigger the migration of other species if located in their vicinity, even if the two bacterial colonies are separated by a barrierFinally, cheaters can arise within cooperator patches by mutation or immigration. Therefore, to investigate the efficacy of migration, the mutation rate value should be 0 to cancel its effect in the meta-population dynamics.22 is a simulation of a population with four types of agents competing for the same resource. It demonstrates many concepts, such as kin selection, cooperation, selfishness, public good, monitoring, punishment, sharing the costs, positive/negative frequency-dependent selection, and multilevel selection. The four agent colors and types: (1) Red: greedy, non-punishing. (2) Orange: greedy, punishing. (3) Turquoise: sustainable, non-punishing. (4) Green: sustainable, punishing.The model is entitled "Evolution, resources, monitoring, and punishment."Punishing agents can perceive other agents in their environment to some degree (perception accuracy) and react to their behavior. There are three kinds of punishment: Punishers can kill agents with greedy harvesting behavior, stop them from harvesting in the next iteration, or have them pay a penalty fee to their neighbors.Agents have a cost (energy) to pay for, both detection and punishment, so this behavior is altruistic. Punisher agents of one type share punishment costs equally.Death rate: the probability that agents die independent of their energy level.Carrying capacity: the maximum amount of resource units on a patch from 1 to 100.Growth rate: the rate at which resources on patches regrow. The maximum sustainable yield is calculated based on the carrying capacity and growth rate.Harvest-sustainable: the number of resource units harvested by sustainable agents.Harvest-greedy: the number of resource units harvested by sustainable agents.Perception accuracy: the probability with which punishing agents notice greedy agents.Costs-perception: the costs in units of energy, punishing agents have to pay for perceiving other agents.Costs-punishment: the costs as units of energy that punishing agents have to pay in each iteration to punish other agents. All punishing agents of an agent divide the costs of punishment.Punishment: the kinds of punishing behavior that punishing agents perform.Fine: if the kind of punishment is "pay fine", the fine in energy units that punished agents have to pay .Living costs and mutation rate: see the first model.The number of patches: There are 60 × 60 patches in the world.The initial energy level of agents is set at living costs + 1.The initial number of resource units on a patch is set to the carrying capacity.The resources on a patch regrow: see the first model.Agents take on their traits (harvest preference and ability to notice and punish) randomly based on the probability of percent-sustainable and percent-punishers.The order in which punishing agents notice greedy agents within one iteration is random.Greedy agents are noticed by punishing agents with a probability of perception accuracy.The order in which detected greedy agents are punished within one iteration is random.Agents produce offspring with a probability of (0.001 × Energy).Agents die with a probability of (death-rate).* In addition to items in the first model.In each iteration, each agent attempts to harvest resources from the patches it is on and the eight neighboring patches until the harvest preference level is reached, except for the punished agent with the sanction (suspend harvest once), its harvest amount = 0 in the current iteration. If the amount of resources available is lower than the amount that the unpunished agent attempts to harvest. Then, the agent moves to a neighboring unoccupied patch with the most resources after losing one energy unit as a move cost.Punishers pay the costs of perceiving the greedy agents. The greedy neighbors have been noticed with the probability of perception accuracy. The agent lost an amount of energy as living costs. The agent dies with the likelihood of death rate or if the energy level falls to zero.If there is an unoccupied neighbor patch, the agent can reproduce with a probability of 0.001 of its energy, place the offspring on the unoccupied neighbor patch, and then transfer half of its energy to its offspring that mutate according to the probability of the mutation rate.Resources regrow on all patches. When the resource amount is more than or equal to 0.1, then it regrows. When the resource is less than 0.1, its value is set to 0.1.Populations (% of carrying capacity): the state of the resource and the agent population in the world as a percentage of total carrying capacity resulting from resource harvesting behavior and resource regrowth, agent reproduction, and death.Average harvest per iteration: the average harvested amounts of agents per iteration by trait, resulting from harvested resource units, minus costs for monitoring and punishing (for punishing agents), minus fines (for punished agents in case of punishment “Pay fine”)The average energy of agents and trait frequencies: see the first model.The model aims to highlight the role of kin selection and punishment mechanisms in supporting cooperation evolution against cheats. We did not need to modify the model but just thought about what the conditional defector should do to upside down the game. The answer was to pay for the escape.For instance, if the standard Harvest-greedy of a cheater  was 13 and the Perception-accuracy of its actual punishers was 75%. Now suppose this cheater faces troubles, and it cannot dominate. However, if it gives up some of its profit to become 12, to escape punishment, and to reduce the perception accuracy to 60%, it could dominate and take over the population.The conditional cheater can pay something and reduce its profit to escape punishment by reducing perception accuracy if there is a positive correlation between these two variables. Therefore, this model is appropriate if it can support/deny such a correlation.Net Logo Behavior Space. All data analyses were carried out via a Python library called Glueviz and Excel.All experiments were carried out under the The default values of the variables: mutation rate = 0 . Dispersal costs = 8 . The agent's shape is Bacteria. Size-Resource-Areas = 4 . Living costs = 1. Percent-Sustainables = 90% . Number-Agents = 80 (started number). Distance-Resource-Areas = 20, (Relatively far). The evolution switch is true . Group dispersal range = 0, 30, 50, 70, 100, 150, and 200.Seven experiments were carried out with 63 runs. Fifteen repeated runs for group dispersal range = 0, and 8 repeated runs for each other value. Approximately all runs with group dispersal range = 0 finished in favor of cooperators and the extinction of cheaters; as expected, cheaters cannot sustain their patches and cannot arrange successful migrations to other patches due to the high dispersal costs.This situation significantly changed in the rest of the runs of group dispersal, ranging from 30 to 200, where cheaters could share the dispersal costs. Consequently, all these runs ended in favor of cheaters, and all cooperators were extinct. Figure The results follow the intuitive predictions that cheaters could thrive, violate the spatial structure mechanism, and dominate the whole meta-population as long as they could cooperate to decrease the dispersal costs.The default values of the variables: mutation rate = 1%. The kinds of Punishment are "suspended harvest once", "pay fine", or "kill". The fine if existed = 5. Carrying capacity = 100. Number Agents = 250, (started number). Costs perception = 0.5. Growth rate = 0.3. Costs-punishment = 0.8 Percent-Punishers = 20%, (started ratio). Harvest-sustainable = 7. Percent-Sustainables = 99% . Living costs = 4. Death rate = 1. Perception-accuracy%. Harvest-greedy   for the punishment types (suspended harvest once and pay fine). However, there were 30,000 ticks for the third type (Kill). The experiments began with a 99% frequency of cooperators, ending with greedy, non-punishing agents taking over the population. The final frequency of greedy non-punishing was above 90% in most runs, and the mean frequency of all steps was above 80% Fig. . We exclOur findings demonstrate a strong positive correlation between the two variables (harvest greed and perception accuracy). The correlation coefficient (r) = 0.99 for the first and second punishment types. (r) = 0.95 for the third punishment type Fig. .Figure 5The selected correlated values led to the dominance of greedy non-punishing agents through the three types of punishment. The dominance of cheaters here means they can violate kin selection and punishment mechanisms when they pay to escape punishment.The frequent dominance of conditional defection strategies in the computational experiments that we have conducted declares the failure of several well-established and crucial mechanisms responsible for augmenting cooperation, such as kin reciprocity, punishment, and spatiality. Therefore, it can be said that maintaining cooperation may be far harder than previously thought.22 we followed paved the way by encapsulating substantial problems of cooperation as well as the most crucial supporting mechanisms. These models aimed to assert the efficient role of kin selection, punishment, and spatial structure mechanisms for supporting cooperators against cheats. The novelty of the present article is that it takes the results to the reverse side by designing the conditional defection strategies and modifying the program codes of the previous models to involve the concept of sharing the dispersal costs. It also reveals the effective behavior of paying to escape different types of punishment.The two models23. In addition, when selfish strategies can modulate benefits and costs, they can outcompete tit-for-tat and generous strategies24. On the other hand, cheaters who can increase their dispersal rate without decreasing the dispersal costs often cannot achieve triumph. Therefore, they cannot drive the cooperators (wild type) to go extinct or even harm themselves if the benefits of exploitation do not offset the costs of dispersal. For instance, the social parasite of P. punctatus ants is a wingless cheater queen. Although it has a high dispersal rate, it has costly migration on foot for long distances. Therefore, the colonies persisted for a long time instead of the supposed rapid collapse of the whole population25.The two forms we presented in this article are simple and general. However, the concept of the conditional defection strategy is much broader. For example, the zero-determinant (ZD) extortion strategy is also a conditional defector strategy if it has a tag-based decision to cooperate with relatives who adopt the same (ZD) extortion strategy but cheat otherwise. At that time, it could be stable and win the game against the opponent's strategies28. However, conditional defectors can violate the crucial mechanisms that support cooperation. Thereby, cheaters take over the population. Then they also go extinct after cooperators because they cannot do the necessary collective actions. Undoubtedly, the production of the common resources or the public good we meant is not independent of cooperators, as in the two models in the present paper. Instead, its production ought to rely on cooperators. For example, the essential excretions of microbes deplete after the extinction of the cooperator. Cheaters can drive the whole population to go extinct; it is a well-established evolutionary prediction. This robust outcome appears in many theoretical and empirical studies and is known as the tragedy of the commons or evolutionary suicide31. This phenomenon can occur if free riders have a fitness advantage over cooperators (wild-type) in an environment set by the cooperators. Creating evolutionary suicide within pathogen populations would mean the end of infections or even endemics, as cheaters are not static chemical substances but infectious transmissible organisms.The findings of the present paper suggest a potentially therapeutic application. Conditional defectors can be used as suicidal agents to drive the population of pathogens into the self-destruction process. From an evolutionary perspective, tumors or microbes are considered populations of cooperating cells that struggle for survival by adopting many collective costly actions to produce the intrinsic common resources32 suggested trojan horse therapy to reduce the virulence of pathogens or release beneficial medical substances inside its colonies.It is not the first time someone has suggested using cheaters in attacking pathogens as a cooperator population. For instance, Brown et al.33 suggested therapeutic interfering particles (TIPs) or hijacker therapy. It is a therapeutic utilization for defective interfering particles (DIPs) that are molecular parasites of viruses or incomplete RNA particles lacking essential packaging elements. It is believed to defeat HIV and other viruses (such as SARS-CoV-2). Moreover, DIPs are antivirals that can be transferred from one person to another until the end of endemicity in infected areas such as sub-Saharan Africa34.Weinberger et al.35 suggested autologous therapy. It aims to increase the diffusion range of the growth factors that the tumor is excreting. Hence, this could increase the tumor's vulnerability to exploitation36.Archetti37 manipulated a defector strain of vesicular stomatitis virus called Δ51. It does not excrete a costly enzyme that suppresses interferon. So it could defeat the wild type. Then led to the tragedy of the commons.Domingo-Calap et al.38.Other treatments and descriptive game-theoretic models of cancer are reviewed hereTo date, many previous papers have suggested closely related ideas. However, the defense mechanisms of cooperators are always a huge obstacle. We think now conditional defector strategies can surpass these obstacles.


Riboflavin presents a competitive inhibition mode with IC50 values in the medium µM range of 79.4 ± 5.0 µM for ZIKV NS2B/NS3pro and 45.7 ± 2.9 μM for YFV NS2B/NS3pro. Against CHIKV nsP2pro, the vitamin showed a very strong effect (93 ± 5.7 nM). The determined dissociation constants (KD) are significantly below the threshold value of 30 µM. The ligand binding increases the thermal stability between 4 °C and 8 °C. Unexpectedly, riboflavin showed inhibiting activity against another viral protein; the molecule was also able to inhibit the viral entry of CHIKV. Molecular dynamics simulations indicated great stability of riboflavin in the protease active site, which validates the repurposing of riboflavin as a promising molecule in drug development against the viruses presented here.Several neurotropic viruses are members of the flavivirus and alphavirus families. Infections caused by these viruses may cause long-term neurological sequelae in humans. The continuous emergence of infections caused by viruses around the world, such as the chikungunya virus (CHIKV) (Alphavirus genus), the zika virus (ZIKV) and the yellow fever virus (YFV) (both of the Flavivirus genus), warrants the development of new strategies to combat them. Our study demonstrates the inhibitory potential of the water-soluble vitamin riboflavin against NS2B/NS3 Neurotropic viruses that trigger neuronal dysfunctions are neuroinvasive or neurovirulent and infect hematopoietic cells, which serve as a platform to gain access to the central nervous system (CNS) via the blood supply ,2. To prEssential for normal cellular functions, growth and development, riboflavin (a water-soluble member of the B-vitamin family—B2) is an underestimated antioxidant that is the precursor of the essential coenzymes flavin adenine mononucleotide (FMN) and flavin adenine dinucleotide (FAD). Riboflavin consists of an isoalloxazine ring bound to a ribose side chain  Supplem and is pOur study is focused on proteases of the three neurotropic viruses ZIKV and YFV (Flaviviridae) and CHIKV (Alphaviridae) due to the large ZIKV, YFV and CHIKV outbreak in South America ,28,29. Tpro) and, in the case of alphaviruses, the nsP2 cysteine protease (nsP2pro). Both proteases represent attractive drug targets due to their essential role in the virus life cycle ) was compared -2,5-diphenyltetrazolium bromide (MTT) assay at a concentration ranging from 1000 to 0.48 µM for 48h. The percentages calculated for the different sample concentrations were plotted and the mean cytotoxic concentration values (CC50) were estimated to be 72.31 µM. . Time-ofp < 0.001), indicating that this compound strongly inhibited the CHIKV entry  of the viral lifecycle is blocked by the molecule, time-of-drug addition experiments were performed. The inhibitory effect of the compound on the viruses’ expressions was assessed in virucidal assay against CHIKV, which decreased 44.35% (±12.49) of CHIKV replication (KV entry . As we dOur results indicate that riboflavin significant reduced CHIKV virus entry to the host cells at non-toxic concentrations. The strong virucidal effect observed for riboflavin in CHIKV might suggest that an anti-CHIKV mechanism of action for this complex might be related to a direct action on the viral particle envelope ,75,76, wNeurotropic flavi- and alphaviruses can cause simultaneous infections in the cases of ZIKV, YFV and CHIKV co-infections by two or all these viruses, which has been previously reported ,83,84,85


BackgroundCoronavirus disease 2019 (COVID-19) vaccination has substantially altered the course of the pandemic, saving tens of millions of lives globally. The problem is that despite such spectacular results, vaccination alone will not be able to control the COVID-19 pandemic because of the rapid evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) even in vaccinated human populations. Therefore, the development of a post-infection, broad-based, orally administered antiviral therapy that would complement vaccination efforts is urgently needed.MethodologyThe so-called viral superinfection therapy (SIT) administers a nonpathogenic attenuated double-stranded RNA (dsRNA) vaccine virus drug candidate, the infectious bursal disease virus serotype R903/78 (IBDV-R903/78) that activates the interferon (IFN) genes, which are the natural, antiviral defense system of host cells.ResultsHere we present two cases of properly vaccinated (with BNT162b2-Pfizer) and booster-dosed COVID-19 patients with vaccine breakthrough infections whose disease duration was shortened to a few days by oral SIT.ConclusionsSIT has already been demonstrated to be safe and effective against five different families of viruses, hepatitis A virus, hepatitis B virus, hepatitis C virus, SARS-CoV-2, and herpes zoster virus. The R903/78 drug candidate is simple to manufacture and easy to administer in an outpatient setting. The expected cost of SIT will be affordable even in resource-limited countries. Vaccination has had a substantial impact on the trajectory of the coronavirus disease 2019 (COVID-19) pandemic. A global reduction of 63% in total deaths (19.8 million from 31.4 million) during the first year of COVID-19 vaccination was achieved ) was dissolved in tap water as instructed by the manufacturer (Ceva-Phylaxia Zrt) and then swallowed in the morning and the same dose again in the evening on March 12, 13, 14, 2022 . The sub-febrile state and fatigue vanished by the second day of treatment. The patient experienced no side effects. The repeated ViVaDiag SARS-CoV-2 Ag Rapid Test on March 15, 2022, proved to be negative. The patient felt physically completely recovered. He performed a functional cardiovascular test, which was a slow pace of 30 minutes of running with an average pulse rate of 130/minute. This is his usual running pace. A couple of hours later his resting pulse rate returned to 58/minute with an SpO2 of 96%. Importantly, four weeks after the IBDV-SIT, the patient’s serum tested positive for anti-IBDV neutralizing antibodies [First, T.B. became ill with mild fever and fatigue. Because the fatigue continued for several days, he performed the ViVaDiag SARS-CoV-2 Ag Rapid Test on March 11, 2022, which proved to be positive. Therefore, T.B. started oral SIT with an attenuated IBDV veterinary vaccine virus, which is commercially available in Hungary. One lyophilized ampoule . The patient experienced no side effects. The repeated ViVaDiag SARS-CoV-2 Ag Rapid Test on March 16, 2022, was still positive, but a day later on March 17, 2022, the Rapid Ag Test became negative. The patient felt physically completely recovered. Therefore, she performed a functional cardiovascular test on March 17, 2022, which was a slow pace of 3.4 km running during which her average pulse rate was 113/minute. A few hours later her resting pulse rate returned to 76/minute with an SpO2 of 96%.E.M. was shivering, had a mild fever and cough, and complained about fatigue, myalgias, nausea, vomiting, headache, weakness, and rhinorrhea on March 15, 2022 (T.B. and E.M. are living together). Her ViVaDiag SARS-CoV-2 Ag Rapid Test proved positive on March 15, 2022. Importantly, during the previous days of her husband’s disease, her ViVaDiag SARS-CoV-2 Ag Rapid Tests proved to be repeatedly negative, indicating that most probably she contracted COVID-19 from T.B. Therefore, she started oral SIT with the same attenuated IBDV veterinary vaccine virus that her husband used before, administering 1 × 10Originally, viral interference referred to the phenomenon when an established viral infection suppressed the replication of a coinfecting virus. While in HBV and HCV-infected patients, it was observed that the replication of the coinfecting virus could also be dominant over the replication of the infecting virus. Dominance can alternate between the two hepatitis viruses but, usually, HBV appears to be suppressed by HCV. Nevertheless, when HBV infection is suppressed by HCV infection, the disease persists and hepatitis remains .Natural viral dominance can be interrupted by direct-acting antiviral (DAA) HCV therapy in patients with HBV/HCV coinfection. Following DAA therapy, HBV reactivation, an abrupt increase in HBV replication, can occur that may result in clinically significant hepatitis. HBV reactivation is a newly identified safety concern in HBV/HCV-coinfected patients who are treated with DAAs. The Food and Drug Administration (FDA), therefore, issued a black box warning that all patients who are being treated with DAA agents for HCV infection must undergo HBV panel testing .When the coinfecting virus does not cause disease, the clinical course is more favorable. Hepatitis G virus (HGV) and GB Virus type C (GBV-C) were identified in the mid-1990s and were proved to be identical. Because this virus does not cause hepatitis despite sharing genome organization with HCV, the virus was renamed “human pegivirus 1” or HPgV-1 for “persistent G” virus. Several studies found that HPgV-1 coinfection was associated with prolonged survival in people living with HIV .Natural coinfection can be imitated by intentionally coinfecting patients with a nonpathogenic virus. Intentional coinfection is called SIT. SIT was developed in the 90s using a conventionally produced attenuated avian vaccine virus, the IBDV, which is a potent activator of the IFN-dependent antiviral gene program Figure .IBDV-SIT has been demonstrated to be safe and effective in 42 acute HBV and HCV patients but also in four decompensated moribund HBV and HCV patients -14. FurtClearly, without controls and with N = 2 it is hard to tell whether the recovery of COVID-19 patients can be attributed to IBDV. However, before COVID-19 vaccines became available, three other COVID-19 patients had also recovered within a few days, including a patient with severe shortness of breath using similar dosages of IBDV  .In the above context, it is important to recall that stimulation of innate immunity by live-attenuated oral enteroviral IFN-inducing vaccine strains (LEV) in large-scale clinical studies involving about 320,000 people provided temporary protection against seasonal influenza and acute respiratory infections (ARI) between 1968 and 1971 in 16 regions of three republics of the former Soviet Union. LEV reduced the morbidity of influenza and ARI by 3.2-fold on average . Recentl0), and their ability to evade existing immunity [By modeling millions of viral sequences across thousands of regions, Obermeyer et al. demonstrated that the SARS-CoV-2 pandemic repeated waves were driven by the emergence of new lineages with higher fitness, affecting their basic reproduction number , it is tempting to speculate that the IBDV R903/78 drug candidate with its IFN activation properties would be promising as anti-SARS-CoV-2 therapy even in severe COVID-19 patients.A major limitation of this study is that the proof-of-principle of SIT in COVID-19 disease was thus far demonstrated by case studies only. While case reports lack statistical analyses, they can provide clinical insights that may be missed in clinical trials . For exaDue to the rapid evolution SARS-CoV-2 virus in human populations including vaccinated people, there is an urgent need for a complementary therapeutic plan “B” to control the COVID-19 pandemic. Here, we present an innovative post-infection strategy: antiviral SIT. SIT orally administers a nonpathogenic attenuated live avian vaccine virus, IBDV, which induces IFNs by its dsRNA genome from within the host cells. The proof of principle of IBDV-SIT has been demonstrated in five different viral infections, HAV, HBV, HCV, SARS-CoV-2, and HZV. The R903/78 drug candidate is simple to manufacture and easy to administer in an outpatient setting. The expected cost of SIT will be affordable even in resource-limited countries.


Dear Editor,The DNA virus known as the monkeypox virus induces monkeypox in both humans and other animals . It is aMacaca fascicularis that were utilized as study animals. The 2003 epidemic in the US was attributed to prairie dogs that were infected by a Gambian pouched rat that was exported from Ghana [Primates and other animals can spread monkeypox virus as they have been found as the incidental hosts of the etiological agent. In 1958, Preben von Magnus found it in om Ghana .The primary difference between the manifestations of smallpox and monkeypox is that smallpox does not result in swollen lymph nodes (lymphadenopathy), but monkeypox does. Monkeypox typically takes 7–14 days to incubate (from inoculation to manifestations), but it can take as little as 521 days. Temperature increased, headaches, neck discomfort, back pain, swollen lymph nodes, chills, and exhaustion are the first symptoms of the illness .Avoid contacting with any animals that might be carrying the virus . Isolate infected individuals from people who could contract the infection by not handling bedding or other items that have come into direct contact with a sick animal. Hands should be washed properly after coming into contact with sick animals or people. Two options include using an alcohol-based hand sanitizer or cleaning hands with warm water and soap. Use personal protective equipment (PPE) when taking care of patients. So, imagine washing your hands. After coming into contact with infectious animals or humans, wash your hands thoroughly . JYNNEOSIt contains any possible outbreaks, making monitoring and early diagnosis identification vital actions that should be considered seriously. Transmission with sick people is the major manifestations for monkeypox virus infection during human monkeypox epidemics. Infected health personnel and household members are at a higher risk. Health professionals managing samples from individuals with a suspicion or confirmed monkeypox infectious agent should adhere to standard infection control practices. If possible, people who have been vaccinated against smallpox should be chosen to care for the patient. Clusters of monkeypox cases were discovered in numerous non-endemic nations in May 2022, with no direct travel links to an endemic location. More research is being conducted to find out the likely source of infection and to prevent further spread. While the origins of this outbreak are being explored, it's critical to consider all possible mechanisms of transmission to protect public health. The handling of samples obtained from individuals and animals suspicious of containing the monkeypox virus should take place in facilities with the necessary expertise. In compliance with WHO guidelines for transporting infectious substances, patient samples must be securely packaged three times before shipping ,8.Not applicable.This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.Fahadul Islam: Conceptualization, Data Curation, Writing - Original Draft, Writing - review & editing. Manish Dhawan: Writing - Original Draft, Writing - review; editing. Talha Bin Emran: Supervision, Writing - Original Draft, Writing - review; editing. All authors critically reviewed and approved the final version of the manuscript.1. Name of the registry: Not applicable.2. Unique Identifying number or registration ID.3. Hyperlink to your specific registration (must be publicly accessible and will be checked): Not applicable.Not applicable.https://orcid.org/0000-0003-3188-2272. E-mail: talhabmb@bgctub.ac.bd.Talha Bin Emran, Ph.D., Associate Professor, Department of Pharmacy, BGC Trust University Bangladesh, Chittagong 4381, Bangladesh. T: +88-030-3356193, Fax: +88-031-2550224, Cell: +88-01819-942214. No specific data collected for the above manuscript.Not commissioned, internally peer-reviewed.All authors report no conflicts of interest relevant to this article.


Vespa orientalis) is spreading across the Italian territory threatening the health and wellbeing of honeybees by feeding on adult individuals and larvae and by plundering hive resources. Considering the capacity of other hornets in harboring honeybee viruses, the aim of this study was to identify the possible role of the Oriental hornet as a vector for honeybee viruses. Adult hornets were subjected to macroscopical examination to identify the presence of lesions, and to biomolecular investigation to detect the presence of six honeybee viruses: Acute Bee Paralysis Virus (ABPV), Black Queen Cell Virus (BQCV), Chronic Bee Paralysis Virus (CBPV), Deformed Wing Virus (DWV), Kashmir Bee Virus (KBV), Sac Brood Virus (SBV). No macroscopical alterations were found while biomolecular results showed that DWV was the most detected virus (25/30), followed by ABPV (19/30), BQCV (13/30), KBV (1/30) and SBV (1/30). No sample was found positive for CBPV. In 20/30 samples several co-infections were identified. The most frequent (17/30) was the association between DWV and ABPV, often associated to BQCV (9/17). One sample (1/30) showed the presence of four different viruses namely DWV, ABPV, BQCV and KBV. The detected viruses are the most widespread in apiaries across the Italian territory suggesting the possible passage from honeybees to V. orientalis, by predation of infected adult honeybees and larvae, and cannibalization of their carcasses. However, to date, it is still not clear if these viruses are replicative but we can suggest a role as mechanical vector of V. orientalis in spreading these viruses.The Oriental hornet ( Apis mellifera , Black Queen Cell Virus (BQCV), Chronic Bee Paralysis Virus (CBPV), Deformed Wing Virus (DWV), Kashmir Bee Virus (KBV), Sac Brood Virus (SBV), in samples of V. orientalis.Among the arthropods which can be identified as natural enemies of ellifera , social ellifera . Three mmetasoma . Orientametasoma . After ametasoma . Betweenmetasoma . Adult hmetasoma , nectar metasoma . In ordemetasoma . Foragermetasoma  and plunmetasoma . Besides hornets . Moreove hornets . In addiIn November 2021, 30 adult Oriental hornets were collected from three different apiaries located in the Campania region . Samples were captured during their predatory activity in the proximity of the hives using a butterfly net. All samples were transported in 50 mL tubes to the laboratory of Veterinary General Pathology and Anatomical Pathology of the Department of Veterinary Medicine and Animal Productions, University of Naples “Federico II” where they were immobilized with chilling for 5 min at -20°C.V. orientalis was also amplified as a housekeeping gene to ensure the presence of amplifiable cDNA in each sample by using the following primer pair designed on the sequence available on GenBank (KF933071.1): V.Orientalis 28S_1 FW: TGGGATGAACCAAACGCAGA, V.Orientalis 28S_1 REV: CTAGTTGCTTCGGCAGGTGA. Moreover, in each PCR reaction, one no template control (NTC) was included as negative control. Honeybees’ samples harboring DWV, SBV, ABPV, BQCV and gBlocks Gene Fragments  mimicking CBPV and KBV intended amplicons were employed as positive controls. Amplification products were then migrated by electrophoresis on 2.5% agarose gel in TAE buffer (Tris-Acetate-EDTA) along with a 100 bp molecular marker (Bioline), stained with ethidium bromide and observed under UV with the ChemiDoc gel scanner (Bio-Rad). Ethical review and approval were waived for this study, as according to the D.L. 4 March 2014 n.26, and national implementing decree following the European regulation 2010/63/UE, ethical approval is not necessary for invertebrates with the except of Cephalopoda.A total of 30 hornets  were then subjected to macroscopical examination by observation at the stereo microscope  in order to identify possible visible alterations, namely crippled wings, shortened and discolored abdomens, which could be indicative of viral infections . RNA wasMacroscopical examination did not reveal any alterations in the examined samples , which could have suggested the presence of viral infection, such as crippled wings, shortened and discolored abdomens. PCR results showed that 28/30 (93%) samples were positive for at least one virus, while no sample was found positive for CBPV. DWV was detected in 25/30 samples (83%), ABPV in 19/30 samples (63%) and BQCV in 13/30 samples (43%). KBV and SBV cDNAs were amplified in 1/30 samples (3%) and 1/30 samples (3%), respectively. 28s ribosomial RNA amplification confirmed the integrity of all analyzed cDNAs.Moreover, several co-infections were identified in 20/30 (67%) samples. Among all, the association between DWV and ABPV was the most frequent , often associated to BQCV . One sample  showed the presence of four different viruses namely DWV, ABPV, BQCV and KBV.For a comprehensive view of PCR positivity and additional co-infections, see Honeybees can be threatened by a great number of pathogens, many of which have been encountered also in other arthropods . SpillovVespula pensylvanica, but MV was also detected in honeybees, suggesting a possible passage from the wild wasp to domesticated honeybees , followed by ABPV (63%) and BQCV (43%), while KBV and SBV were present only in one sample each. No other virus was identified in our samples. Our results are in line with previous data, in fact, among the viruses most frequently found in non-honeybee arthropods, DWV is the most detected, while BQCV, ABPV, SBV and KBV result highly present, however with lower frequency  and parasite infestation, and suppose that they become infected by predating infected adult honeybees and larvae, and cannibalizing their carcasses. As a matter of fact, the viruses found in our hornet samples are also the most widespread in the apiaries across the Italian territory (V. orientalis. However, as honeybee viruses can be transmitted via honey (V. orientalis in spreading these viruses.To date many viruses which can infect honeybees have been reported and the list is continuously increasing , also duoneybees . Social s of DWV , BQCV anvelutina , as wella crabro . It has oulbrood . This strequency . Moreoverequency , as wellividuals . Conversividuals , none ofividuals . In honeividuals  as well structor . Accordierritory  and the erritory , suggestia honey  we shoulThe original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author.Conceptualization, KP and PM; Methodology, KP and GA; Validation, MM and PM; Writing—Original Draft Preparation, KP; Writing—Review and Editing, MM and PM; Supervision, MM and PM. All authors read and approved the final version of this manuscript.The authors received financial support from the research funding of the Department of Veterinary Medicine and Animal Productions, University of Naples "Federico II" Italy.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.


People with disabilities are more likely than individuals without disabilities to face higher levels of deprivation and multidimensional poverty, and those deprivations might be associated with the extra costs of living with a disability. However, there has not been an analysis of how multidimensional poverty measures are related to the extra costs of disability or whether these measures can be used as a proxy of the standard of living in the analysis of the extra costs of disability. This paper aims to analyse whether multidimensional poverty measures can be used to study the extra costs of disability and, based on the capability approach, how multidimensional poverty is related to the extra costs of disability. This paper discusses theoretical, technical, and methodological aspects to be considered when studying the relationship between extra costs and multidimensional poverty, and we used data from Chile and Nigeria to illustrate this relationship. We conclude that when analysing the extra costs of disability, multidimensional measures might be an option; however, it is necessary to clearly stablish the relationship among income, deprivation, and the extra costs of disability.  The design of inclusive social protection programmes for people with disabilities requires information to be obtained from a variety of sources, and it necessitates, for example, disaggregating data by disability status, understanding the socioeconomic characteristics of persons with disabilities, and recognising their specific needs. The analysis of the disability-related costs faced by individuals and households has become a priority for a range of countries in order to define the scope and level of support that people with disabilities should receive and to estimate their levels of poverty.Studies analysing the extra costs of disability have used a variety of methodological approaches to study the relationship among extra cost, disability, and income ,2. One aGood and Services Required (GSR) uses focus groups and qualitative methods to provide important information on the main extra costs of disability and how different types of functional limitations are associated with different costs and coping strategies. However, only a few countries have implemented this method and use it to inform policy decisions related to disability benefits. GSR uses expert groups of people with disabilities, who provide a comprehensive list of goods and services that they need and require . The Standard of Living (SoL) method estimates the extra direct costs of disability and calculates the extra income that a household or an individual with disabilities needs in order to have the same standard of living as that of a person without disabilities . A systeWhen applying the SoL method, two main variables have been used to define the standard of living. The first follows Filmer et al. and uses principal components to compute a wealth index, which is a proxy of consumption . The secBoth variables impose assumptions on the relationship between income and disability. On the one hand, when the wealth index is used, it is assumed that a reduction in income will be directly related to a reduction in the value of the wealth index. On the other hand, when using subjective questions about material deprivations, we assume that the main reason for not having an item is lack of money. Although these assumptions have theoretical and empirical justifications, it is important to consider that in the case of disability, the relationship between extra cost and income is mediated by an individual’s opportunities to generate and use income. In the past decade, there has been an increase in the number of studies analysing the levels of multidimensional poverty experienced by people with disabilities and their families. Most studies have found that they are more likely to be poorer and to face a higher number of deprivations, compared with persons without disabilities and their families ,12,13,14In the context of the analysis of extra costs, multidimensional poverty measures can offer an opportunity to capture how disability affects other aspects of life and how those might increase a person’s risks of facing extra costs and becoming poor. Until now, multidimensional poverty measures have not been used to analyse the extra costs of disability and have not been evaluated to see if these measures are a good proxy of the standard of living and how the analysis can be implemented. In addition, it is important to define how the extra costs of disability increase the risk of deprivation and how being deprived in a specific indicator increases the risk of facing higher extra costs associated with disability and an increased risk of deprivation in other indicators. This is how the disability–deprivation/poverty cycle starts and persists. This paper has two main purposes: first, to analyse whether multidimensional measures can be an option in the study of the extra costs of disability using the SoL method and second, to discuss how the additional costs related to disability are associated with multidimensional poverty. The article first introduces the SoL method and the most important theoretical and methodological assumptions behind it. It then considers what multidimensional poverty measures are and how they are designed and computed. This is followed by a discussion about the relationship between multidimensional poverty and the extra costs of disability; we ask which theoretical and methodological aspects need to be considered when thinking of using a multidimensional poverty measure in the analysis of the extra costs of disability, and we offer an illustration of how these aspects should be considered in the analysis. The Standard of Living (SoL) method aims to analyse the relationship between living with a disability and household consumption levels . The metOne of the most important assumptions of this model is that two individuals with the same income level experience different living standards if one has a disability and the other does not. This is assumed to be the case because the person with disabilities will spend more on the consumption of disability-related items and will therefore reduce the overall consumption of other items, an aspect that will affect his/her standard of living ). The concept of standard of living is fundamental for this method and its operationalisation. Therefore, the variable that captures this concept should reflect objects of value  and it sThe SoL method only aims to capture the average direct costs of disability. It assumes that people with disabilities have different needs from those unaffected by disability and that therefore they prioritise those needs and reduce their consumption of nondisability-related items. However, the relationship between income and consumption is not as direct as the SoL method assumes. Indeed, although income is one of the most important determinants of consumption, credit accessibility, psychological factors, and the ability to pay for and buy products are also significant determinants of consumption . In conclusion, the SoL method allows for the analysis of the relationship among standard of living, income, and disability. However, it ignores important determinants of consumption, such as individual needs, preferences, access to credit or savings, and the supply of services that enable people to consume different goods. As a result of ignoring these important aspects, people with disabilities living in low-income countries have presented lower extra costs of disabilities compared with disability-affected people living in countries with higher incomes and levels of human development. However, these results do not reflect the reality that confronts people living with disabilities, and given the limitations of the SoL, it is not possible to analyse the potential effect that extra costs of disabilities have on the lives of individuals with disabilities and their families. Therefore, a measure that is sensitive to the context and can be tailored to it is necessary in order to capture the real effect of the extra costs of disability on the standard of living of individuals.A range of perspectives for understanding poverty has been adopted in the literature. According to Ringen 1988), measures of poverty can be divided into direct and indirect measures [88, measuMultidimensional poverty measures are considered to be direct measures of poverty because they capture the actual deprivations that a person or a household faces in a specific moment. Multiple methods to measure multidimensional poverty exist in the literature. However, in the past decade, the Alkire–Foster (AF) method has become one of the most popular and is frequently used to measure multidimensional poverty . The AF 0). The incidence represents the percentage of people who are multidimensionally poor; the intensity represents their average number of deprivations, and M0 represents the percentage of potential deprivations that poor individuals face, allowing for the total possible number of deprivations of the society in question [The AF method computes three main measures: the incidence of multidimensional poverty (H), its intensity (A), and the adjusted headcount ratio . Living standards: In this dimension, it is important to consider access to the services and their use. Higher accessibility costs will increase the risk of deprivation in access to a clean water source and improved sanitation, as well as to the Internet and other modern technology.A multidimensional poverty measure can include deprivations in aspects that may be affected by the extra costs of disability, for example, considering a measure with four dimensions and 11 indicators . TherefoIt is not possible to assume that higher levels of deprivation are only the result of the extra costs that a person might face. Indeed, deprivations in access to school attainment or attendance can result from other factors, such as attitudinal and physical barriers, which go beyond a person’s (or a household’s) ability or opportunity to pay for different services. In addition, although the evidence suggests that on average individuals with disabilities face higher deprivations in one or more indicators and usually their levels of deprivation are more severe than those of people without disabilities, this will not be the case for all people with disabilities in a specific context. Finally, using a multidimensional poverty measure as a proxy of standard of living would not make it clear how income compensation can reduce deprivation, especially in cases where the deprivation is created by social or environmental factors, which go beyond an individual’s own control. For example, even if households that include disability-affected members are compensated with a certain amount of income, that will not compensate them for the general lack of accessible transportation systems or the lack of schools or health providers in the community.A range of aspects should be discussed when considering whether a multidimensional poverty measure can be used as a proxy for the standard of living in the analysis of the extra costs of disability. First, theoretical arguments are associated with how the concept of standard of living is understood. The second aspect is related to understanding the relationship between income and deprivation, the role of income in reducing deprivation, and how this role can be (or not be) captured in the analysis of the extra costs of disability, using a multidimensional measure. The third and final aspect is to understand what a multidimensional poverty measure represents, what aspects of poverty are captured, and the main aspects to consider when designing a measure for people with disabilities. The first aspect to consider is how poverty and standard of living are defined. Under the capability approach, which understands well-being in terms of capabilities and functionings, where capabilities are the doings and beings that people can achieve if they so choose and functionings are capabilities that have been realised ‘poverty’ is the lack of basic capabilities , and ‘stThe SoL method assumes that a person with a disability has a lower standard of living because she/he reduces her/his consumption of different goods because of the need to afford disability-related expenditures. Thus, we are assuming that there is a direct relationship between disability and consumption and that individuals with and without disabilities have the same preferences and will decide to consume similar items. However, when this assumption is analysed in terms of the concept of multidimensional poverty, an important role is played by aspects related to the opportunities available in the society, how services are provided, and the preferences of individuals and families. For example, it is difficult to assume that an individual will not have access to clean water because he/she needs to increase his/her disability-related consumption. In this case, access to a clean water source will be mediated by the existence of piped water services in the neighbourhood or the provision of other protected water sources, such as a protected spring or well, and although there is a possibility that people with disabilities do not have access to the source of water, this barrier is not the result of favouring the consumption of water above the consumption of other disability-related goods. Although there is a relationship between income and deprivation, being deprived in nonmonetary aspects is mediated by other factors, which might reduce or increase the potential effect of lack of income. In terms of the capability approach, income is seen as a means but not as an end. In addition, it is recognised that in order to be able to transform income into achievements, conversion factors play a major role. Conversion factors—which influence how people can turn means into ends—can be classified as personal, social, and environmental. The first one depends on the person’s circumstances, for example, disability. The second factor is social conversion aspects related to the society where the person lives; one example is class or caste. The third and final group consists of environmental conversion factors that capture the physical environment where the person lives, such as geographical location . Policy makers can change conversion factors, mainly social and environmental factors, by implementing social policies to reduce environmental barriers or discrimination, which might increase the possibilities of social participation. Moreover, policies can also target people with different individual conversion factors, such as people with disabilities, and provide access to services and benefits to improve their quality of life. Given the existence of conversion factors, income compensation is not the only or best solution to reduce deprivations. Indeed, an income transfer cannot be effective in the case of countries that do not provide inclusive services, such as education or health care. Amartya Sen gives an example of a conversion factor directly related to disability ,42. UndeIn the context of multidimensional poverty, the role of environmental and social factors is vital, because two individuals with the same levels of multidimensional poverty may have a different combination of deprivations and, most importantly, the circumstances that created those deprivations might be different. Therefore, it will be unfair to say that the same income compensation can compensate for deprivations in health  or in education .In conclusion, the magnitude of the potential effect of income on deprivation depends on a range of factors that might affect how income affects deprivations. Individual, social, and environmental factors play an important role in defining whether a person is deprived and in which particular aspects of development. Thus, it is fundamental to incorporate those aspects into the analysis in order to capture the problem’s complexity and potential circumstances. As discussed above, multidimensional measures are direct measures of poverty, which include aspects related to deprivations in various aspects of life. Most measures include deprivations in terms of health care, education, living standards, and employment. The number and type of indicators depend on the purpose of the measure and the available data. One limitation of the multidimensional measures is that no measure can include all dimensions of poverty, and there are trade-offs between indicators. Additionally, depending on the weight structure, indicators considered in multidimensional poverty measures can be defined as supplements or complements. For example, consider the global multidimensional poverty index, which has three dimensions and ten indicators. Each dimension has the same weight (1/3), and each indicator inside the dimension has the same relative weight. Therefore, indicators in the health and education dimensions have the same weight, and a weight almost three times than one indicator in the living standards dimension. In this context, a person who is deprived in terms of access to water, sanitation, and electricity has the same level of deprivation as a person who is deprived in terms of child mortality or school attendance. Therefore, when analysing a multidimensional poverty measure, it is important to consider what represents a specific level of deprivation. For example, if two people have a counting vector that is the number of weighted deprivations that a person faces, equal to 40%, each of them might have a different combination of indicators distributed among dimensions. Consequently, policy makers should be able to identify trade-offs among dimensions and indicators and how those are related to the extra costs of disability. In addition, it is important to identify how deprivations limit the achievement of different capabilities and functionings, how extra costs can create different deprivations, or how deprivations in one aspect create extra costs that increase the probability of being deprived in other indicators. Aiming to illustrate the previous discussion, we used data from Chile and Nigeria. We selected Chile because it is a high-income country, with levels of multidimensional poverty lower than 20% and with national policies to guarantee the rights of people living with disabilities. Nigeria was included in the analysis because, contrary to Chile, the country has high levels of deprivation and multidimensional poverty, and although there are policies to protect the rights of persons with disabilities, given the high levels of poverty of the country, those might have a reduced impact on the lives of persons affected by disabilities. In Chile, we used the Socioeconomic Conditions Survey 2017 and in Nigeria the Living Standard Survey 2019/2020. In the case of Chile, we computed the National MPI for Chile , and in Once we had computed the MPI, we estimated the extra costs of disability using the SoL method for persons 18 or older. The dependent variable was the counting vector (or the sum of weighted deprivations per household) of the multidimensional poverty measure; as independent variables, we used the following factors: the existence of a member with disability in the household (following the Washington Group (WG) definition), household income, size of the household, region, area of residence, and gender of the head of the household. In each of the countries, the model used robust standard errors. The results of the analysis reveal that there Is a negative relationship between increasing the number of deprivations and the income level of the household. In addition, there is a positive association between households with at least one member with disabilities and the number of deprivations that the household faces. These signs are different from the ones usually identified in the SoL method, where disability is usually associated with a lower standard of living, and the standard of living variables are positively associated with income. However, when we computed the coefficient related to the extra costs of disability, the ratio is negative, although the negative sign is produced by the negative association between income and the sum of deprivations. In addition, it is important to analyse the relationship between the different indicators of the MPI by levels of income and to disaggregate the MPI by disability status of the household. When we disaggregated the types of deprivation faced by households with disabled members according to their income level, we found important differences between income quintiles in the case of Chile. For example, in the lowest income quintiles, households with and without members with disabilities face similar deprivations as households without members with disabilities (except in the pension and environment indicators) . By contIn both countries, the multidimensional poverty measures were computed at the household level, and they included deprivations that affected members with and without disabilities in the household. It is not possible to easily identify whether the person with disability is the one creating the deprivation. Therefore, it is not possible to assume that the higher levels of multidimensional poverty are directly related to disability and that an increase in the levels of household income would compensate for the extra costs of disability and reduce multidimensional poverty. For example, in the case of Chile, when we computed the ratio between the disability and the income coefficients, the results reveal that it is necessary to have a 35.1% income compensation because of the extra costs associated with disability. However, if we analyse the combination of deprivations faced by households with members with disabilities, we find that the two pairs of indicators with the higher percentage of households with disabilities deprived are (1) contribution to social security and years of schooling and (2) habitat and years of schooling. In both cases, it is not possible to define directly whether these deprivations are the results of a disability or were produced before the disability occurred. In the case of Nigeria, the ratio between the coefficients of disability and income was equal to 13.1%. Thus, households with at least one member with disabilities will need an increase in their income equal to 13.1%. In addition, in Nigeria, the types of deprivation affecting the largest percentage of persons with disabilities were (1) food security and cooking fuel and (2) cooking fuel and housing. In these four deprivations, it is not possible to assume that the deprivations are the result of the extra costs of disability and that income compensation will cover the extra costs of disability and directly reduce levels of deprivation. A multidimensional measure will enable a clearer analysis of the potential loss of welfare faced by individuals because of their disabilities. In this case, the assumption will not be whether individuals with disabilities reduce their consumption of different items because of the increase in the consumption of disability-related items; instead, the main assumption is that different factors associated with barriers that persons with disability face might reduce their well-being or increase their levels of poverty and deprivation, for example, discrimination, stigma, social exclusion, and lack of participation. Define the measure at the individual level. Thus, use the individual as the unit of identification and analysis. This will directly identify individual deprivations and achievements and allow us to assume that higher levels of deprivations or lower levels of achievements are directly related to disability or the extra costs of disability.Include indicators that reflect achievements for the whole society, disregarding individual characteristics, such as race, ethnicity, or disability, for example, the level of education that a person is expected to achieve in a specific country.Clearly define the trade-offs among indicators. For example, suppose that the measure includes five dimensions and 20 indicators equally weighted. In that case, it is important to define which indicators have a higher or lower relative importance and how those levels might affect the results of the measure.In this case, it is not necessary to define an optimal level of well-being or poverty (or to compute the incidence of well-being). Ideally, one should analyse the counting vector or the weighted sum of indicators.The challenge is then to establish how income compensation can improve lower levels of achievement in important aspects of social, human, and economic development and whether income is the only aspect that social policies can change to guarantee that persons with disabilities can participate in society. In this case, it will be important to analyse that the relationship between multidimensional measures and the extra costs of disability depends on the opportunities available in the society in question and that those opportunities will mediate in the achievement of different capabilities and functionings.This analysis will allow us to go beyond income compensation and understand that the extra costs of disability have a negative impact on the levels of capabilities and functioning that a person can achieve or limit the opportunities open to people living with disabilities of living the life that they would like to live. Whether realised or not, extra costs affect the opportunities of individuals with disabilities in general to access services that will facilitate income generation and their equal participation in society. The AF method provides an opportunity to design a measure that is tailored to the context. It includes indicators that capture the desirable levels of achievement in different aspects of human, social, and economic development. However, to properly capture well-being, the following procedures are necessary: It is recommended to estimate regressions by income quintiles; thus, the sample can be stratified, and an income coefficient is computed for each quintile. It is expected that in the highest quintile, the income compensation will be lower. However, because the level of individual well-being is the result not only of consuming specific assets or goods but also of the person’s access to opportunities, people with disabilities will face barriers in all income quintiles, and so they will still face lower levels of well-being.The inclusion of the education dimension should be considered, depending on the context. Endogeneity problems exist, given that higher educational levels are associated with higher income. However, it will be advisable to explore what is the contribution of this dimension to the well-being measure and to conduct robustness tests to analyse how changes in the structure affect the results.The dimension of employment aims to capture access to good-quality jobs and life–work balance, which is not directly associated with income levels. It is recommended that this dimension includes indicators related to satisfaction with employment or underemployment (inadequate jobs for their training). The objective of this dimension is to identify if the person has a job that matches his/her qualifications.Other options of indicators are social and family support, social capital, trust, and inclusion in decision making.Depending on the country’s development levels, the dimension of living standards can be included in the multidimensional measure.In addition, the following aspects might be considered, if this multidimensional measure is used in methods, such as SoL: Finally, it is expected that people with disabilities face lower levels of well-being because they face different social, economic, attitudinal, and physical barriers. Although it is expected that an absolute well-being measure, which uses objective indicators, will better capture the potential impacts of the extra costs of disability, it will be necessary to empirically test the measure and the relationship with the extra costs of disability.As has been discussed, multidimensional measures can provide information related to the deprivations or achievements faced by individuals with disability and how those can vary depending on the disability status and the severity of the disability. In addition, multidimensional measures provide information on how external barriers can affect individual achievement levels. Contrary to other measures usually used to analyse the extra costs of disability , multidimensional measures are absolute measures whose main structure and relative contribution are defined on the basis of normative arguments. In the case of the wealth index, it is not possible to know which indicators or factors contribute the most to the index . Therefore, it is not possible to know which indicators are negatively associated with disability. In addition, when using the wealth index in the SoL method, the results will reveal how much more income a household with a disability needs in order to have the same economic resources to acquire non-disability goods and services as enjoyed by a household without a disability. It implies that giving them money equivalent to the extra costs will allow them to purchase the same assets and have the same level of economic well-being. In the case of multidimensional measures, the analysis of the extra costs will tell us which potential income compensation is needed to equalise the well-being of a person with a disability. Nevertheless, this income compensation will need to be complemented by providing opportunities to access services. However, a person will need to receive income compensation; this might vary depending on other factors . Thus, multidimensional measures provide more information related to the levels of deprivation experienced by individuals. In addition, these measures can provide information regarding the income compensation that a person needs to have a similar level of well-being and which other policies should be implemented to guarantee the inclusion of persons with disabilities in similar conditions to those experienced by a person without a disability. The SoL of persons with disabilities and their families is directly affected by the extra costs associated with disability. However, how much this is reflected in the SoL method depends on the context and the levels of opportunities that individuals in a society have. Although considering using multidimensional poverty measures when analysing the extra costs of disability can be an option, aspects related to the relationship between the extra costs of disability and different levels of deprivation should be explicitly mentioned and discussed. Furthermore, it is important to analyse how income compensation can reduce deprivation and how individual, social, and environmental factors can affect the potential effect of that compensation on the lives of persons with disabilities. Analysing the potential effect of extra costs of disabilities on their levels of well-being will benefit from the use of a multidimensional well-being measure, which is a concept that goes beyond the standard of living and can include aspects related to access to opportunities. This measure aims to capture different aspects of life that are desirable for every individual (with and without disabilities). Given that it is tailored to the context, it is expected that even in countries with lower levels of socioeconomic development, it will be possible to analyse the potential effect of extra costs on the well-being of individuals with disabilities. In addition, this measure goes beyond income and tries to include aspects of life that are affected by direct, indirect, and opportunity costs associated with disabilities and how these limit the opportunities of individuals living with disability in a specific society.