Infected Population Research Articles

The role of natural recovery category in malaria dynamics under saturated treatment.

In the process of malaria transmission, natural recovery individuals are slightly infectious compared with infected individuals. Our concern is whether the infectivity of natural recovery category can be ignored in areas with limited medical resources, so as to reveal the epidemic pattern of malaria with simpler analysis. To achieve this, we incorporate saturated treatment into two-compartment and three-compartment models, and the infectivity of natural recovery category is only reflected in the latter. The non-spatial two-compartment model can admit backward bifurcation. Its spatial version does not possess rich dynamics. Besides, the non-spatial three-compartment model can undergo backward bifurcation, Hopf bifurcation and Bogdanov-Takens bifurcation. For spatial three-compartment model, due to the complexity of characteristic equation, we apply Shengjin's Distinguishing Means to realize stability analysis. Further, the model exhibits Turing instability, Hopf bifurcation and Turing-Hopf bifurcation. This makes the model may admit bistability or even tristability when its basic reproduction number less than one. Biologically, malaria may present a variety of epidemic trends, such as elimination or inhomogeneous distribution in space and periodic fluctuation in time of infectious populations. Notably, parameter regions are given to illustrate substitution effect of two-compartment model for three-compartment model in both scenarios without or with spatial movement. Finally, spatial three-compartment model is used to present malaria transmission in Burundi. The application of efficiency index enables us to determine the most effective method to control the number of cases in different scenarios.

Gold Nanoparticle-Based Colorimetric and Fluorescent Dual-Mode Lateral Flow Immunoassay for SARS-CoV-2 Detection.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection caused the COVID-19 pandemic, impacting the global economy and medical system due to its fast spread and extremely high infectivity. Efficient control of the spread of the disease relies on a fast, accurate, and convenient detection system for the early screening of the infected population. Although reverse transcription-quantitative polymerase chain reaction (RT-qPCR) is the gold-standard method for SARS-CoV-2 RNA analysis, it has complex experimental procedures and relies on expensive instruments and professional operators. In this work, we proposed a simple, direct, amplification-free lateral flow immunoassay (LFIA) with dual-mode detection of SARS-CoV-2 RNA via direct visualization as well as fluorescence detection. The viral RNA was detected by the designed DNA probes to specifically hybridize with the conserved open reading frame 1ab (ORF1ab), envelope protein (E), and nucleocapsid (N) regions of the SARS-CoV-2 genome to form DNA-RNA hybrids. These hybrids were then recognized by the dual-mode gold nanoparticles (DMNPs) to produce two different readout signals. The fluorescence characteristics of different sizes of GNPs were explored. Under the optimized conditions, the LFIA presented a linear detection range of 104-106 TU/mL with a limit of detection (LOD) of 0.76, 1.83, and 2.58 × 104 TU/mL for lentiviral particles carrying SARS-CoV-2 ORF1ab, E, and N motifs, respectively, in the fluorescent mode, which was up to 10 times more sensitive than the colorimetric mode. Furthermore, the LFIA exhibited excellent specificity to SARS-CoV-2 in comparison with other respiratory viruses. It could be used to detect SARS-CoV-2 in saliva samples. The developed LFIA represents a promising and convenient point-of-care method for dual-mode, rapid detection of SARS-CoV-2, especially in the periods with high infectivity.

A fractional modeling approach to a new Hepatitis B model in light of asymptomatic carriers, vaccination and treatment

Hepatitis B virus (HBV) is a much more threatening and prolonged disease than hepatitis A. It can start as an acute disease, but in roughly 5 to 10% of situations, it can progress to a chronic condition that permanently damages the liver. After getting or coming into contact with the Hepatitis B virus (HBV), the said symptoms normally last from 10 days to 6 months. In the present paper, to have a firm understanding of the dynamics of HBV, we derived a new fractional model in the Caputo sense with asymptomatic carriers, vaccination, and treatment classes. We obtain the basic reproduction number R0 for the diagnosis and recurrence of the disease. We determine the stability of the proposed model locally and globally for R0 values less than and greater than 1. We use the Lyapunov function theory in fractional environments to establish the global stability of the fractional Hepatitis B virus (HBV) model. We demonstrate the existence and uniqueness of the fractional-order model. To look at the fractional order model’s solution graphically, we used a useful numerical strategy to get more detailed numerical results for the factors that have a big effect on getting rid of diseases. Additionally, the inclusion of the treatment class in the population allows for the determination of the impact of alternative medicines used to treat infected populations. Numerical simulation of the proposed fractional order (FO) Caputo model is performed, allowing for the analysis of graphical representations and the significance of fractional order derivatives to illustrate the impact of our theoretical findings.

Modeling and stability analysis of substance abuse in women with control policies

Substance abuse is considered to be predominantly a problem for all in society, and much substance abuse research is done with a male majority. Recent drug addiction studies, however, reveal that there are substantial gender variations in substance-related epidemiology. The epidemiology of women’s substance misuse raises issues distinct from those addressed by men’s substance abuse. Women with addictions are more likely than males to experience several impediments to accessing and entering substance misuse treatment. In this regard, we framed a mathematical model by considering the whole population as a women population. For this system, we found pair of equilibrium points namely the Addiction-free equilibrium point and the Non-trivial equilibrium point. Moreover, the addicts generation number (threshold parameter) RA has been found to investigate the spread of addiction. Also, the local and global stability analysis for both the equilibrium points have investigated. Further, to analyze the decrease and increase of the infected population and recovery population respectively, an optimum control analysis is done with two control parameters using Pontryagin’s maximum principle. The influence of addict generation numbers on significant parameters involved in RA has been shown. An optimum control study projected that social media awareness is substantially more efficient than the fixed control in optimizing drug addiction among women. Through numerical simulations we have exhibited, the effect of with and without control on each population. Finally, it produced positive efficacy by reducing the number of infected and increasing the rehabilitation population.

Efficacy and safety of omadacycline for treating complicated skin and soft tissue infections: a meta-analysis of randomized controlled trials.

In the present study, we aimed to compare the clinical efficacy and safety of omadacycline (OMC) with its comparators for the treatment of complicated skin and soft tissue infections (cSSTIs) in adult patients. Randomized controlled trials (RCTs) evaluating OMC for cSSTIs were searched in databases of PubMed, Embase, Cochrane, Web of Science, and Clinical Trial, up to July 2022. The primary outcomes were clinical efficacy and microbiological response, with secondary outcome was safety. Four RCTs consisting of 1,757 patients were included, with linezolid (LZD) as a comparator drug. For clinical efficacy, OMC was not inferior to LZD in the modified intent-to-treat (MITT) (OR: 1.24, 95% Cl: [0.93, 1.66], P = 0.15) and clinically evaluable (CE) populations (OR: 1.92, 95% Cl: [0.94, 3.92], P = 0.07). For microbiological response, OMC was numerically higher than LZD in the microbiologically evaluable (ME) (OR: 1.74, 95% Cl: [0.81, 3.74], P = 0.16) and microbiological MITT (micro-MITT) populations (OR: 1.27, 95% Cl: [0.92, 1.76], P = 0.14). No significant difference was found in subpopulations of monomicrobial or polymicrobial mixed infection populations. The mortality and adverse event rates were similar between OMC and LZD. OMC was as good as LZD in terms of clinical efficacy and microbiological response, and has similar safety issues in treating cSSTIs. OMC might be a promising option for treating cSSTIs in adult patients.

Optimal control of a multi-scale HIV-opioid model.

In this study, we apply optimal control theory to an immuno-epidemiological model of HIV and opioid epidemics. For the multi-scale model, we used four controls: treating the opioid use, reducing HIV risk behaviour among opioid users, entry inhibiting antiviral therapy, and antiviral therapy which blocks the viral production. Two population-level controls are combined with two within-host-level controls. We prove the existence and uniqueness of an optimal control quadruple. Comparing the two population-level controls, we find that reducing the HIV risk of opioid users has a stronger impact on the population who is both HIV-infected and opioid-dependent than treating the opioid disorder. The within-host-level antiviral treatment has an effect not only on the co-affected population but also on the HIV-only infected population. Our findings suggest that the most effective strategy for managing the HIV and opioid epidemics is combining all controls at both within-host and between-host scales.

Exploring Biochemical and Hematological Variations in Malaria Cases: A Retrospective Analysis at a Health Center at Mumbai City India

Introduction: In Mumbai, an overpopulated metropolis with tropical conditions, malaria poses a persistent challenge, particularly in damp slum areas. Despite reported declines in death and incidence rates, the city faces a significant burden. Our project focuses on an unusual aspect: a heightened incidence among males, especially during sporadic monsoon outbreaks and in areas undergoing extensive redevelopment. Through an epidemiological survey of infected populations in municipal clinics, supported by microscopic, hematological, and microbiological evidence, we aim to provide insights into this atypical pattern. Materials and Methods: A cross-sectional, partly retrospective study was designed with participants being sourced from regional slums and chawls, during the immediately preceding three-year period of project completion. Patients attending OPDs were randomly selected from amongst those with febrile symptoms related to malarial disease and tested. Symptomatic individuals were tested for malaria microscopically using peripheral blood smear (PBS) and confirmed by employing the malaria antigen test (RMAT). Blood urea by enzymatic method and serum creatinine by Jaffes method. Results: Out of 1651 participants, 8.18% were malaria-positive, predominantly males (87.41%). P. vivax was the main parasite (87.41%), followed by P. falciparum (6.67%) and mixed infections (5.93%). ANOVA revealed significant RBC count differences (F = 6.32, p = 0.003). Tukey's HSD test showed P. vivax patients had higher RBC counts than mixed infection (p = 0.002), while P. falciparum counts were similar to P. vivax (p = 0.089) but higher than mixed infection (p = 0.014). Predominance of P. vivax emphasizes its impact on RBC counts and diagnostic complexities. The p values indicate that for all parameters, except serum creatinine in males, there is a statistically significant difference in the mean values between the malaria positive and negative groups Conclusion: This study highlights high malaria prevalence in urban India, with males more susceptible, possibly due to increased mosquito exposure. P. vivax is predominant, aligning with national data, emphasizing the need for tailored control measures. Surprisingly, P. vivax is associated with higher RBC counts than P. falciparum or mixed infection, suggesting differences in erythrocytic cycles. These findings have critical implications for regional malaria management, prompting further research into underlying mechanisms.

Age Structured Deterministic Model of Diphtheria Infection

Age-structured mathematical model of diphtheria infection has been formulated with specific epidemiological classes such as S1, susceptible infant at time t (0-1years), S2, susceptible school children population at time t, V, vaccination population at time t, E, exposed population at time t, I1, asymptomatic infection population at time t, I2, symptomatic infection population at time t, ID, detected infectious humans at time t (asymptomatic and symptomatic) population through testing, R, recovered population at time t. It was established through theorems and proofs that the model is epidemiologically meaningful, and that all its state variables are positive (non-negative) at time t>0 in the domain ℘, and that the domain ℘ is indeed bounded. Using the next generation matrix, the reproduction ratio Rb of the system was determined. Using dynamical system theory, it was established that the system is locally stable. A matrix-theoretic method was used in the construction of an appropriate Lyapunov function for the global stability analysis of the formulated model, and also established that the system is globally asymptotically stable if Rb≤1 and unstable otherwise.

Comprehensive evaluation on progressive development strategies in DENV surveillance and monitoring infection rate among vector population.

The elevated rise in dengue infection rate has been a health burden worldwide and it will continue to impact global health for years to come. Accumulated literature holds accountable the geographical expansion of the mosquito species transmitting the dengue virus DENV. The frequency of this viral disease outbreaks has increased rapidly in the recent years, owing to various geo-climatic and anthropological activities. Due to scarcity of any effective control measures, there has been a continuous traceable rise in mortality and morbidity rates. However, it has been reported that the spate of incidences is directly related to density of the virus infected vector (mosquito) population in a given region. In such a scenario, systems capable of detecting virus infected vector population would aid in estimating prediction of outbreak, as well as provide time to deploy suitable management strategies for vector control, and to break the vector-human transmission chain. This would also help in identifying areas, where much improvement is needed for vector management. To this context, we illustrate an exhaustive overview of both gold standards and as well as emerging advents for sensitive and specific mosquito population strategized viral detection technologies. We summarize the cutting-edge technologies and the challenges faced in pioneering to field application. Regardless the proven popularity of the gold standards for detection purpose, they offer certain limitations. Thus with the surge in the infection rate globally, approaches for development of newer advancements and technique upgradation to arrest the infection escalation and for early detection as a part of vector management should be prioritized.

Beyond acute infection: molecular mechanisms underpinning cardiovascular complications in long COVID.

SARS-CoV-2, responsible for the global COVID-19 pandemic, has manifested significant cardiovascular implications for the infected population. These cardiovascular repercussions not only linger beyond the initial phase of illness but have also been observed in individuals who remain asymptomatic. This extended and pervasive impact is often called the post-acute COVID-19 syndrome (PACS) or "Long COVID". With the number of confirmed global cases approaching an alarming 756 million, the multifaceted challenges of Long COVID are undeniable. These challenges span from individual health complications to considerable burdens on worldwide healthcare systems. Our review comprehensively examines the complications of the persistent cardiovascular complications associated with COVID-19. Furthermore, we shed light on emerging therapeutic strategies that promise to manage and possibly mitigate these complications. We also introduce and discuss the profound concerns regarding the potential transgenerational repercussions of SARS-CoV-2, emphasizing the need for a proactive and informed approach to future research and clinical practice.

COVID-19 reinfections in Mexico City: implications for public health.

Since its appearance, COVID-19 has immensely impacted our society. Public health measures, from the initial lockdowns to vaccination campaigns, have mitigated the crisis. However, SARS-CoV-2's persistence and evolving variants continue to pose global threats, increasing the risk of reinfections. Despite vaccination progress, understanding reinfections remains crucial for informed public health responses. We collected available data on clinical and genomic information for SARS-CoV-2 samples from patients treated in Mexico City from 2020 epidemiological week 10 to 2023 epidemiological week 06 encompassing the whole public health emergency's period. To identify clinical data we utilized the SISVER (Respiratory Disease Epidemiological Surveillance System) database for SARS-CoV-2 patients who received medical attention in Mexico City. For genomic surveillance we analyzed genomic data previously uploaded to GISAID generated by Mexican institutions. We used these data sources to generate descriptors of case number, hospitalization, death and reinfection rates, and viral variant prevalence throughout the pandemic period. The fraction of reinfected individuals in the COVID-19 infected population steadily increased as the pandemic progressed in Mexico City. Most reinfections occurred during the fifth wave (40%). This wave was characterized by the coexistence of multiple variants exceeding 80% prevalence; whereas all other waves showed a unique characteristic dominant variant (prevalence >95%). Shifts in symptom patient care type and severity were observed, 2.53% transitioned from hospitalized to ambulatory care type during reinfection and 0.597% showed the opposite behavior; also 7.23% showed a reduction in severity of symptoms and 6.05% displayed an increase in severity. Unvaccinated individuals accounted for the highest percentage of reinfections (41.6%), followed by vaccinated individuals (31.9%). Most reinfections occurred after the fourth wave, dominated by the Omicron variant; and after the vaccination campaign was already underway. Our analysis suggests reduced infection severity in reinfections, evident through shifts in symptom severity and care patterns. Unvaccinated individuals accounted for most reinfections. While our study centers on Mexico City, its findings may hold implications for broader regions, contributing insights into reinfection dynamics.

A simulation study to assess the epidemiological impact of pneumonia transmission dynamics in high-risk populations

The term “high-risk population” refers to individuals with an increased likelihood of contracting a severe illness or disease due to factors such as age, underlying medical conditions, pregnancy, geographical location, or a combination of these factors. This paper proposes a mathematical model of pneumonia focusing on the high-risk infected population: children under five years of age and adults over 65 years. A mathematical analysis is presented, and numerical simulations are conducted to investigate the impact of various model parameters on infection rates within each subpopulation. We employed Latin hypercube sampling for a global sensitivity analysis using the number of infectious individuals as a response function to identify the most influential parameters on the infection dynamics. Numerical results suggest that prompt and effective treatment at the onset of the disease is essential to control the spread of pneumonia among children under five and adults older than 65.

Leptospirosis Relative Risk Estimates based on Continuous-Time, Discrete-Space Stochastic SIR-L-SI Transmission Model

Leptospirosis is a re-emerging global disease that has become endemic in Malaysia. The transmissions usually occur between animals especially rats to rats and rats to humans. Since, it is an easily contractable disease that can be transmitted directly through contact with infected rat’s urine or indirectly from the environment such as via water and soil, it is very challenging to curb this disease from infecting humans. Poor understanding of the disease and lack of epidemiological data also made leptospirosis is difficult to control. To cope with this problem, a leptospirosis disease transmission model is developed to study the mechanism of leptospirosis disease spread over continuous-time that may help to predict future caused of an outbreak. This study aims to construct a continuous-time and discrete-space stochastic SIR-L-SI (Susceptible, Infected, Recovered Humans-Leptospires in the Environment-Susceptible, Infectious Rats) of leptospirosis disease transmission to estimate the risk involved. A simple method of asymptotic and numerical analyses is applied as an alternative approach for solving simultaneous differential equations in the leptospirosis SIR-L-SI transmission model. The application of the proposed model is demonstrated using leptospirosis data for Malaysia. The results of asymptotic behaviour and numerical analysis provide useful information about susceptible and infective rat and human populations as well as offer relative risk estimates that can be used as one of the control measures in identifying hot-spot areas for this disease.

Individual and temporal variation in movement patterns of wild alpine reindeer and implications for disease management

Animal behaviour is important for prevalence and outbreaks of infectious diseases, for instance by affecting individual interactions. Increasing the knowledge of individual movement patterns can provide better insight into disease prevalence and spread, helping to target efforts to minimise disease outbreaks. Chronic wasting disease (CWD) is a fatal prion disease affecting cervids. CWD is transmitted by animal‐to‐animal contact and through the environment, thus individual variation in space use and social associations may influence disease transmission patterns and infection risk. CWD was detected in Norwegian alpine reindeer Rangifer tarandus tarandus in 2016, and eradication of the infected population was implemented. A 3:1 infection rate between males and females suggests sex‐specific behavioural drivers. We utilised an extensive individual‐based dataset of 149 GPS‐marked wild reindeer to investigate individual variation in movement patterns in terms of inter‐ and intra‐annual home range size and site fidelity, and variation in home range overlap and distances between individuals. We aimed to identify patterns which could indicate higher potential disease risk. Females had larger annual and seasonal home ranges than males, except during calving and rut. Greater home range overlaps and shorter between‐individual distances were found between same‐sex individuals than different‐sex individuals, except during the rut. Accordingly, the rut season stands out with greater male home ranges, greater home range overlap and shorter distances between males and between males and females, which could indicate that this season is critical for disease transmission. Measures to prevent disease spread should lower contact rates, e.g. by reducing the abundance of adult males before they mix with other groups during the rut. This can be achieved for instance by allowing earlier hunt on adult males when they are distributed in small male groups, to reduce the transmission risk and keep disturbance of other individuals low.

Ventilation shutdown and the breath-taking violence of infectious disease emergency management in industrial livestock production

Powerful ventilation systems are a crucial technology in industrial livestock production, mitigating the unhealthy ambient conditions that result from great densities of animal bodies, biowastes, and chemical agents, and enabling the rapid production of massive quantities of flesh and eggs in such crowded indoor spaces. But bad air is just one of many biophysical and technoscientific challenges managed in these spaces, chief among them the ever-present risks of infectious disease transmission and evolution that threaten animal health and productivity and pose untold risks for humans. This article examines the intersection of these two central problems, where ventilation systems that are normally used to manage bad air within enclosures have been repurposed in the context of disease outbreaks to quickly and cheaply kill infected populations by hyperthermia. An analysis of this nascent practice, euphemistically termed “ventilation shutdown,” shows how governments and publicly funded scientific institutions have worked with private industry to develop and systematize the use of this and other technologies of mass death to respond to infectious disease emergencies, a dynamic that, we argue, sheds new light on both the precarity and the violence of industrial livestock production.

Analysis of age-specified and genotype distribution of HPV multiple infections in the Chinese population.

Multiple infections are a key component of HPV pathogenesis and have a direct impact on how an infection turns out. It's crucial to look at the associations between HPV multiple infections and both age and HPV genotypes in the Chinese population, searching for the causative factors of multiple infections with a view to providing new ideas for the treatment and prevention of multiple infections. In this study, we retrospectively analyzed the data of HPV infections among outpatients from the 2019year to the 2021year of Shandong Maternal and Child Health Hospital. Analyzed the correlation between HPV multiple infections and age using logistic regression. Differences in the percentage of multiple infections between age groups were compared using the chi-square test. The chi-square test compared the differences in the distribution of 15 common HPV genotypes in mono- versus multiple infections. A two-dimensional matrix presented the frequency of HPV genotype combinations. Logistics regression analysis showed that age was significantly associated with the occurrence of multiple infections, with a dominance ratio OR 1.026 (95% CI 1.02-1.04). Interestingly, the proportion of HPV multiple infections among HPV-positive individuals increases with age in people older than 30years of age. The chi-square test showed there was a difference in the distribution of HPV genotypes between multiple infections and mono- HPV infection (χ2 = 76.4; p = 0.000), a difference in the composition of HPV genotypes for dual versus single infections (χ2 = 90.6; p = 0.000) and a difference in HPV genotypes for triple versus single infections (χ2 = 56.7; p = 0.000). A 2 × 2 matrix showed that the combination of HPV52/HPV58 (30; 6.4%) was the combination of the highest frequency of infection for dual infections; The HPV52/HPV58 (21; 4.8%) combination was the highest frequency of HPV tripleinfection combination. HPV multiple infections were positively correlated with age; increasing age was positively correlated with the proportion of HPV multiple infections in the total infected population; the distribution of the 15 common genotypes of HPV differed between multiple infections and single infections; and HPV52:58 was a common type of infection combination in the Shandong population.

Kontrol Optimal pada Model Penyebaran SARS-CoV-2 dengan Pelaksanaan Testing dan Perawatan

COVID-19 (Corona Virus Disease 2019) is a disease of the respiratory system caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The COVID-19 pandemic was declared active by WHO in March 2020 and the pandemic status was lifted on May 5, 2023. COVID-19 must still be watched out to prevent a new wave of pandemics, so an optimal control analysis is needed. The purpose of this study is to determine the optimal control form of the SARS-CoV-2 spread dynamics model in minimizing the number of exposed populations by implementing testing and minimizing the infected population by implementing treatment. Optimal control analysis is carried out using the Pontryagin Maximum Principle, while numerical calculations for simulation use the Forward-Backward Runge-Kutta method with the help of MATLAB R2021a software. The results of the optimal control analysis conducted on 3 simulations with different vaccination values and incubation periods show that the application of both control strategies to the COVID-19 spread model in Indonesia is effective in reducing the number of infected individuals to 99.9%, but cannot maintain the population size.

PENYELESAIAN MODEL PENYEBARAN PENYAKIT ISPA DENGAN MENGGUNAKAN METODE RUNGE KUTTA FEHLBERG DI PROVINSI SULAWESI SELATAN

This stud discusses the analysis and simulation of acute respiratory infection (ISPA) in South Sulawesi Province by applying the RLTSM used the Fehlberg’s Runge-Kutta method. The research is an applied research type with the aim of obtaining a model of the spread of acute respiratory infection and knowing the numerical solution of the mpdel in predicting cases future acute respiratory infection. The mathematical model for acute respiratory infection is in the farm of a system of diffrential equations that includes the variables R (Susceptible), L (Exposed), T (Infected), S (Recovered), dan M (Death). The research results obtained in 2023 with h=0,01 years using the Fehlberg’s Runge-Kutta method with initial values of R0 =458.665, L0 = 165.670, T0 = 141.755, S0 = 103.217, M0 = 9 is R100 =681.560, L100 = 107.068, T0 = 141.755, S100 = 167.445, M100 = 25.248, for order 4 results and R100 =681.559, L100 = 107.070, T100 = 57.208, S100 = 167.442, M100 = 25.247, for order 5 results. The rate of the susceptible population has increased, the exposed and infected population has decreased, the recovered population has increased and then decreased, and the death population has increased and then stabilized

A hospitalization mechanism based immune plasma algorithm for path planning of unmanned aerial vehicles

Unmanned aerial vehicles (UAVs) and their specialized variants known as unmanned combat aerial vehicles (UCAVs) have triggered a profound change in the well-known military concepts and researchers from different disciplines tried to solve challenging problems of the mentioned vehicles. Path planning is one of these challenging problems about the UAV or UCAV systems and should be solved carefully by considering some optimization requirements defined for the enemy threats, fuel or battery usage, kinematic limitations on the turning and climbing angles in order to further improving the task success and safety of autonomous flight. Immune plasma algorithm (IP algorithm or IPA) modeling the details of a medical method gained popularity with the COVID-19 pandemic has been introduced recently and showed promising performance on solving a set of engineering problems. However, IPA requires setting the control parameters appropriately for maintaining a balance between the exploration and exploitation characteristics and does not design the particular treatment and hospitalization procedures by taking into account the implementation simplicity. In this study, IP algorithm was supported with a newly designed and realistic hospitalization mechanism that manages when an infected population member enters and discharges from the hospital. Moreover, the existing treatment schema of the algorithm was changed completely for improving the efficiency of the plasma transfer operations and removing the necessity of IPA specific control parameters and then a novel path planner called hospital IPA (hospIPA) was presented. For investigating the performance of hospIPA on solving path planning problem, a set of detailed experiments was carried out over twenty test cases belonging to both two and three-dimensional battlefield environments. The paths calculated by hospIPA were also compared with the calculated paths of other fourteen meta-heuristic based path planners. Comparative studies proved that the hospitalization mechanism making an exact discrimination between the poor and qualified solutions and modified treatment schema collecting the plasma being transferred by guiding the best solution give a tremendous contribution and allow hospIPA to obtain more safe and robust paths than other meta-heuristics for almost all test cases.

An unusual diarrheal outbreak in the community in Eastern Thailand caused by Norovirus GII.3[P25

BackgroundSentinel laboratory surveillance for diarrheal disease determined norovirus to be the most common cause of non-bacterial gastroenteritis in people during the COVID-19 pandemic in Thailand. An increase in patients presenting with diarrhea and vomiting in hospitals across Chanthaburi province between December 2021 and January 2022 led to the need for the identification of viral pathogens that may be responsible for the outbreak.MethodsFecal samples (rectal swabs or stool) from 93 patients, of which 65 patients were collected during the December 2021 to January 2022 outbreak, were collected and screened for viral infection by real-time RT-PCR. Positive samples for norovirus GII were then genotyped by targeted amplification and sequencing of partial polymerase and capsid genes. Full genome sequencing was performed from the predominant strain, GII.3[P25].ResultsNorovirus was the most common virus detected in human fecal samples in this study. 39 of 65 outbreak samples (60%) and 3 of 28 (10%) non-outbreak samples were positive for norovirus genogroup II. One was positive for rotavirus, and one indicated co-infection with rotavirus and norovirus genogroups I and II. Nucleotide sequences of VP1 and RdRp gene were successfully obtained from 28 of 39 positive norovirus GII and used for dual-typing; 25/28 (89.3%) were GII.3, and 24/28 (85.7) were GII.P25, respectively. Norovirus GII.3[P25] was the predominant strain responsible for this outbreak. The full genome sequence of norovirus GII.3[P25] from our study is the first reported in Thailand and has 98.62% and 98.57% similarity to norovirus found in China in 2021 and the USA in 2022, respectively. We further demonstrate the presence of multiple co-circulating norovirus genotypes, including GII.21[P21], GII.17[P17], GII.3[P12] and GII.4[P31] in our study.ConclusionsAn unusual diarrhea outbreak was found in December 2021 in eastern Thailand. Norovirus strain GII.3[P25] was the cause of the outbreak and was first detected in Thailand. The positive rate during GII.3[P25] outbreak was six times higher than sporadic cases (GII.4), and, atypically, adults were the primary infected population rather than children.