Safeguard Public Health Research Articles

One Health Perspectives on Food System Transformation: Insights from the InsectERA Agenda

Abstract Background One Health framework recognises the interconnectedness of human, animal, plant and environmental health. With this understanding, it becomes imperative to address challenges such as those posed by food systems through a One Health lens. Food systems pose significant public health challenges, particularly in terms of food safety and security. Pressures from factors such as population growth, changing consumption patterns and intensified production systems, particularly animal-based protein production, contribute to environmental pressures. In addition, environmental changes, including climate change, further threaten food safety and access to healthy food. Methods Through the InsectERA agenda, funded as part of the Recovery and Resilience Plan, stakeholders collaborated across sectors to explore the potential of insects as bioindustrial tools to address food system challenges. A structured, integrated approach combining health and sustainability considerations was matured and applied to pilot food products developed through this initiative. Recognising the potential health and sustainability impacts of these products, a comprehensive assessment was carried out. Results This study defined a structured, integrated approach to assessing the health and sustainability impacts of foods developed under the InsectERA agenda. Key steps included i) identifying critical issues and questions, ii) prioritising considerations, iii) defining methodologies, iv) collecting and analysing data, and v) integrating results for communication. Conclusions The study highlights the importance of integrated approaches in addressing food system transitions. Integrated approaches, guided by the One Health framework, play a critical role in informing policy decisions by providing policy makers with robust evidence. There is an urgent need for food system transformation based on decisions that holistically consider health and sustainability impacts, to ensure the protection of Public Health. Key messages • Integrating health and sustainability into the transition of food systems, within the One Health framework, is crucial for identifying options that safeguard Public Health. • A structured, integrated approach within a multi-stakeholder environment offers robust insights for policy decisions, advancing sustainable food systems.

Machine learning for air quality index (AQI) forecasting: shallow learning or deep learning?

In this study, several machine learning (ML) models consisting of shallow learning (SL) models (e.g., random forest (RF), K-nearest neighbor (KNN), weighted K-nearest neighbor (WKNN), support vector machine (SVM), artificial neural network (ANN), and deep learning (DL) models (e.g., long short-term memory (LSTM), gated recurrent unit (GRU), recurrent neural network (RNN), and convolutional neural network (CNN)) have been employed for predicting air pollution and its classification. The models were selected based on factors such as prediction accuracy, model generalization, model complexity, and training time. Our study focuses on analyzing and predicting the air quality index (AQI) using daily PM10 concentration as natural pollutants and nine meteorological parameters from March 2013 to February 2022 in Zabol. We also utilized the information gain (IG) method for feature selection. Several measures including accuracy, F1 score, precision, recall, and the area under the curve (AUC), are computed to assess model performance. This study demonstrates the efficacy of DL models, particularly CNN, in predicting the AQI with remarkable accuracy. Our findings reveal that all models effectively classify air quality levels, with an AUC of 0.95 for the good class in both DL and ANN models, significantly outperforming SL models. The AUC values for the hazardous and moderate classes of DL models were also impressive, at 0.90 and 0.83, respectively, underscoring their effectiveness in critical classifications. In terms of performance, CNN achieved an accuracy of 0.60, leading the models, while RF followed closely at 0.58. RNN, GRU, ANN, and SVM each reached an accuracy of 0.57, demonstrating a competitive edge. LSTM and WKNN recorded an accuracy of 0.55, and KNN was slightly lower at 0.53. These results highlight the superior capabilities of DL models in addressing complex air quality classifications, providing invaluable insights for policymakers. By leveraging these advanced techniques, stakeholders can implement more effective strategies to combat air pollution and safeguard public health. It is worth noting that irregular monitoring of air quality data may affect the robustness of our predictions, highlighting the need for more consistent data collection to ensure an accurate representation of pollution levels.

Mpox in East Africa: Learning from COVID-19 and Ebola to Strengthen Public Health Responses

The Africa Centers for Disease Control and Prevention declared mpox a Public Health Emergency of Continental Security (PHECS) in Africa. African public health systems have moved to mobilize a response against a backdrop of inherent significant challenges. With this commentary, we discuss how lessons from past public health emergencies, particularly COVID-19 and Ebola outbreaks, have prepared the region for improved disease surveillance, rapid response strategies, and effective public health communication and how these lessons can be applied to the mpox response, emphasizing the importance of strong healthcare infrastructure, effective data sharing, community engagement, targeted interventions, and robust contact tracing. Additionally, addressing misinformation and building public trust are crucial for controlling the spread of any disease. By leveraging these strategies, African countries can enhance their response to mpox. This includes improving diagnostic capabilities, strengthening cross-border collaborations, and prioritizing vaccination campaigns where needed. Ultimately, by applying the hard-earned lessons from the COVID-19 pandemic and Ebola outbreak, the East Africa region can better address the challenges posed by mpox and safeguard public health.

Pharmaceuticals and personal care products contamination in the rivers of Chennai city during the COVID-19 pandemic.

Pharmaceuticals and personal care products (PPCPs) monitoring in surface water is crucial to address the escalating threat of antimicrobial resistance and safeguard public health. This study aimed to investigate the occurrence of 21 different PPCPs, including wastewater chemical markers, antibiotics, and parabens in the surface water of Chennai city using Ultra Performance Liquid Chromatography-Triple Quadrupole Mass Spectrometry (UPLC-MS/MS) analysis. It is noteworthy that chemical markers viz., carbamazepine (CBZ) and caffeine (CAF) were detected in all the sites and contributed to more than 95% of the total PPCPs load indicating a significant intrusion of wastewater. Among the antibiotics, fluoroquinolones were dominant in this study. Interestingly, a significant and strong correlation was seen between fluoroquinolones, CBZ and CAF (R2 = 0.880-0.928, p < 0.05), suggesting similarities in their sources. More than 50% of the sites exhibited a risk for antimicrobial resistance (RQAMR) withRQAMR > 1 for ciprofloxacin, indicating a significantpublic health concern. The ecotoxicological risk assessment of PPCPs showed no risk to any organisms, except for triclosan, which posed a risk to fish and daphnids at one sitenear an open drain in Buckingham canal.

Impact of lead and nickel contamination on metabolic health: Associations with diabetes mellitus in a pakistani cohort

Environmental exposure to heavy metals, particularly lead (Pb) and nickel (Ni), is implicated in chronic metabolic diseases, including diabetes mellitus (DM). This cross-sectional study assessed the Pb and Ni levels in groundwater using ICP-OES and urine samples collected from 2688 participants using ICP-MS. We aimed to establish the associations between Pb and Ni exposure and risk factors for DM and metabolic disorders. Groundwater analysis revealed the elevated levels of total dissolved solids, electrical conductivity, hardness, turbidity, Ni, and Pb, exceeding the WHO guidelines. The mean concentration of Pb in groundwater samples of study area was 0.025 mg/L which was higher than the WHO permissible limit of 0.01 mg/L. Similarly the mean concentration of Ni in groundwater samples of study area was 0.038 mg/L which was also higher than the WHO permissible limit of 0.02 mg/L. In human study, participants, categorized into Pb-detected and Ni-detected groups, exhibited significantly higher Pb and Ni levels and non-exposed non-diabetic groups. Ni-detected diabetics showed elevated Ni levels compared to non-exposed non-diabetics. Similarly, Pb-detected diabetics showed elevated Pb levels compared to non-exposed non-diabetics. These findings suggest a potential contribution of Pb and Ni exposure to DM development. The study also identified associations between heavy metal exposure and disruptions in various biomarkers related to DM, lipid profile, inflammation, oxidative stress, liver function, and kidney function. Pb-detected diabetics demonstrated elevated levels of glycemic index biomarkers, including fasting blood glucose (P < 0.0001) and HbA1c (P < 0.0001). Ni-detected diabetics exhibited increased inflammatory markers, such as CRP (P < 0.0001) and IL-6 (P < 0.0001). Both Pb and Ni exposure were associated with dyslipidemia, as indicated by elevated levels of total cholesterol (P < 0.0001) and LDL (P < 0.0001). Additionally, heavy metal exposure was linked to impaired liver and kidney function, supported by elevated levels of AST (P < 0.0001), ALT (P < 0.0001), creatinine (P < 0.0001), and blood urea nitrogen (P < 0.0001), with Pb exposure also associated with higher levels of MDA (P < 0.0001). Correlation analyses demonstrated significant associations between urinary Pb and Ni concentrations and various biomarkers related to DM and metabolic disorders. In conclusion, this study provides substantial evidence linking Pb and Ni exposure to the development of DM and metabolic disorders in a Pakistani population, emphasizing the need for strict regulations and preventive measures to reduce heavy metal contamination and safeguard public health. Future longitudinal studies and interventions are warranted to elucidate mechanistic links between heavy metal exposure and metabolic diseases.

Reexamining exposure from truck emissions considering daily movement of individuals

With the growing demand for urban freight transportation, trucks emit a large amount of pollutants such as particulate matters and nitrogen oxides, increasingly affecting public health. This study establishes a modelized air dispersion structure to simulate pollutant concentration distribution. By integrating multiple data sources including mobile phone signals and satellite images, we reconstruct the daily trajectories of individuals and further incorporate simulated pollution concentrations in calculating dynamic and static exposure of individuals to truck emissions. Econometric models considering spatial dependence are developed to evaluate the influencing factors and elucidate the mechanisms of pollutant exposure. Results show factors including freight demand, road network, residential and employment locations, personal commuting distance, and population age structure matter in assessing truck emission exposure. As a result, a mixture of vehicular emission standards, urban traffic control, land planning, and industrial policies is proposed to reduce truck pollutant exposure and safeguard public health.

Mercury Screening for At-Risk Populations

This article discusses the risks associated with mercury exposure, particularly focusing on at-risk populations in Canada, such as those living in remote areas, individuals living near toxic spills, and those who rely on fish consumption year-round. It underlines the detrimental health effects of mercury exposure, including liver and kidney damage, neurological changes, and developmental issues. The lack of awareness and screening for elevated mercury levels is identified as a significant issue along with the need for greater education regarding possible exposures to mercury. A screening pathway is proposed to aid primary care providers in identifying individuals at risk of elevated mercury levels, with the aim of preventing long-term health complications. Overall, the paper highlights the importance of proactive measures to mitigate mercury exposure and safeguard public health.

How Advocates Can Use the Revised Circular A-4 Means to Push for Stronger Worker and Environmental Protections.

For public interest advocates engaged on issues of worker health and safety and environmental protections, regulatory cost-benefit analysis has long been seen as an obstacle to meaningful progress. In November 2023, the Biden administration overhauled Circular A-4, which provides guidance to agencies on how to perform cost-benefit analyses for their rules. The reforms seek to make cost-benefit analysis less biased against worker safety, public health, environmental, and other protective safeguards. As such, the new version of Circular A-4 offers important new levers to agencies to justify more stringent protections. By extension, those in the public interest community can use agency implementation of the new Circular A-4 as part of their advocacy efforts for specific rules they are tracking. This article seeks to support this tactic by providing a roadmap for advocates on how to incorporate into their comments critiques of agencies' cost-benefit analyses based on the Circular A-4 revisions.

Improving the short-term prediction of dissolved carbon monoxide using a combination of Light GBM and meta-heuristic algorithms

In this study, the prediction of carbon monoxide pollutants on a short-term scale has been investigated according to some input data sources, comprising gas concentrations related to air quality and weather features. Utilizing a hybrid modeling approach that integrates the Light Gradient Boosting Machine with several meta-heuristic optimization algorithms such as Chaos Game Optimization, Aquila Optimizer, and others, we aimed to optimize the hyperparameters of the Light GBM to enhance predictive accuracy. The application of a K-fold cross-validation technique with K=5 helped in preventing overfitting. By conducting a case study on a real dataset collected from a gas multi-sensor device, it was found that the hybrid model combining the Light Gradient Boosting Machine with Chaos Game Optimization demonstrated superior performance compared to other models. The values of the coefficient of determination, Root Mean Square Error, Mean Absolute Error, and Mean Absolute Percentage Error for this model based on test data are 0.99, 0.0393, 0.0301, and 0.0052, respectively. These results underscore the effectiveness of the hybridization approach in providing highly accurate predictions for short-term carbon monoxide concentrations, offering a valuable tool for environmental monitoring and enhancing public health safeguards.

Climate Change Projections for Stroke Incidence in Taiwan: Impact of 2°C and 4°C Global Warming Level.

This study aimed to establish the exposure-lag-response effect between daily maximum temperature and stroke-related emergency department visits and to project heat-induced stroke impacts under global warming levels (GWL) of 2°C and 4°C. Stroke-related emergency department visits in Taiwan from 2001 to 2020 were identified using the National Health Insurance Research Database (NHIRD). The study population consisted of 1,100,074 initial stroke cases matched with 2,200,148 non-stroke controls. We employed Distributed Lag Nonlinear Models (DLNM) in a case-crossover study to investigate the association between temperature and stroke. Generalized Estimating Equations (GEE) models with a Poisson function were used to correlate high-temperature exposure with annual stroke incidence rates. Projections were made under two global warming scenarios, GWL 2.0°C and 4.0°C, using Coupled General Circulation Model (GCMs). Baseline data from 1995 to 2014 were transformed for spatial distribution at the township level. Geographic Information System (GIS) spatial analysis was performed using Quantum GIS 3.2.0 software. DLNM exposure-lag-response effect revealed that daily maximum temperature exceeding 34°C significantly increased the risk of stroke-related emergency department visits, particularly for ischemic stroke. Under the 2°C GWL scenario, the frequency of days with temperatures surpassing 34°C is projected to rise substantially by the median year of 2042, with a further increase to 92.6 ± 18.0 days/year by 2065 under the 4°C GWL scenario. Ischemic stroke showed the highest increase in temperature-related incidence rates, notably rising from 7.80% under the GWL 2°C to 36.06% under the GWL 4°C. Specifically, the annual temperature-related incidence rate for ischemic stroke is expected to increase significantly by 2065. Regions such as Taichung, Hsinchu, Yilan, and Taitung demonstrated pronounced changes in heat-related ischemic stroke incidence under the GWL 4°C. The findings emphasize the importance of addressing temperature-related stroke risks, particularly in regions projected to experience significant temperature increases. Effective mitigation strategies are crucial to reduce the impact of rising temperatures on stroke incidence and safeguard public health.

Dengue In Brazil: Challenges And Strategies For Public Health Management

This academic essay explores the complex landscape of dengue in Brazil, a viral arbovirus transmitted by the Aedesaegypti mosquito, with significant impacts due to its high incidence and frequent epidemic outbreaks, especially during warm and rainy periods conducive to vector reproduction. The symptoms range from high fever and muscle pain to severe forms such as dengue hemorrhagic fever, requiring urgent medical intervention. The country's dengue control strategies include eliminating breeding sites, using insecticides, and conducting public awareness campaigns. The disease not only strains healthcare services but also adversely affects the economy and social well-being, underscoring the importance of robust epidemiological surveillance systems and coordinated responses. Initiatives such as the Health in Schools Program (PSE) and the roles played by Community Health Agents (ACS) and Endemic Disease Control Agents (ACE) are crucial in prevention and control efforts. Collaborative efforts across health, education, and community sectors are essential to address the challenges of dengue comprehensively. Therefore, Brazil must continue investing in research, vaccines, and innovative strategies to sustainably and effectively reduce the burden of dengue and safeguard public health.

Selection of antibiotic-resistant bacterial populations in the dairy cow gut following intramuscular ceftiofur treatment for metritis

Third-generation cephalosporins such as ceftiofur are critically important antibiotics because human pathogens with resistance to these drugs contribute to high mortality rates. These antibiotics are also frequently given to dairy cattle for treating infections, emphasizing the critical role they play in both human and veterinary medicine. To investigate the impact of intramuscular ceftiofur treatment on the concentration of resistant bacteria in the gut, we focused on cows with metritis, a common bacterial infection that frequently requires antibiotic intervention. Twelve cows with metritis (cases) were enrolled and treated with intramuscular ceftiofur for 5 d along with 12 matched healthy cows that were not given ceftiofur (controls). Fecal samples were collected weekly from cows in both the case and control groups for 4 weeks, starting before the treatment of the case group. Five fecal samples per cow were used for analysis (n = 120 samples). The abundance of Gram-negative bacteria was quantified per sample after plating on MacConkey agar, which was also used to quantify the abundance of Gram-negative bacteria with resistance to ceftiofur, ampicillin, and tetracycline. Interestingly, the case cows with metritis had a greater abundance of Gram-negative bacteria than the control cows just before treatment, but no difference in abundance was observed between groups at wk 1-4. The abundance of ceftiofur-resistant Gram-negative bacteria was also similar between the case and control cows immediately before treatment of the cases. However, a significant increase in abundance of ceftiofur-resistant Gram-negative bacteria was observed in the case cows 1-week after treatment that persisted through wk 3. Although the recovery of ampicillin- and tetracycline-resistant bacteria was similar between the 2 groups post-treatment, cases had significantly higher levels of ampicillin-resistant bacteria before treatment. Collectively, these findings demonstrate that intramuscular ceftiofur treatment can affect the abundance of cultivable Gram-negative bacteria and select for ceftiofur-resistant populations that can persist for up to 3 weeks. Judicious use practices are needed to ensure that ceftiofur and other critically important antibiotics are administered only when necessary to minimize the spread of resistance and safeguard public and animal health.

Rapid detection of murine-derived ingredients in meat products using real-time enzymatic recombinase amplification.

Accurate identification of meat species is critical to prevent economic fraud and safeguard public health. The use of inappropriate meat sources, such as murine, poses significant health risks because of potential contamination with pathogens and allergens, leading to foodborne illnesses. The present study aimed to develop a novel real-time enzymatic recombinase amplification (ERA) method for the rapid and specific detection of murine DNA in meat products. A novel ERA primer and probe set was designed, targeting a murine-specific single-copy nuclear gene identified through bioinformatics analysis. The assay demonstrates high specificity, showing no amplification in commonly consumed meats, other animals or major crops. Additionally, it exhibits remarkable sensitivity, detecting as few as five copies of murine genomic DNA. For practical application, the ERA method could effectively identify mouse DNA in laboratory-prepared samples at concentrations as low as 0.5% and also quantify samples with mouse DNA content as low as 5%. It also accurately detects the presence of murine-derived ingredients in commercially available meat products. The detection process is straightforward, utilizing a simple isothermal device for incubation, blue light excitation and a smartphone camera for result interpretation. This rapid analysis can be completed within 20 min. The newly developed real-time ERA method provides a valuable tool for standardizing meat trade practices, promoting food safety and enhancing consumer confidence in the authenticity of meat products. © 2024 Society of Chemical Industry.

Heavy Metal Biomonitoring in Cultured Rainbow Trout of the Black Sea and Risk Estimations on Its Consumption.

In recent years, the growing importance of fish species obtained through aquaculture, coupled with a decline in wild-caught fish, has raised concerns about the potential accumulation of pollutants in these fish. This work aimed to analyze the amounts of elements in trout cultured mainly between Sinop and Samsun shores at the south of the Black Sea and marketed in Sinop fish markets. The comparison of these values with national and internationally accepted regulations was conducted, and evaluation of health risks for consumers was performed. Oncorhynchus mykiss samples were bought in April, May, and June of 2022 and 2023. The heavy metal concentrations were determined using inductively coupled plasma mass spectrometry (ICP-MS). Fish tissues were wet digested in Teflon vessels. The outcomes were contrasted with established regulatory limits for heavy metals in fish. Fortunately, the metal concentrations detected in the fillets were found to be below the permissible levels set by regulations, indicating that the fish were not significantly contaminated. Furthermore, the estimated daily intake (EDI) and target hazard quotient (THQ) values, which are utilized to evaluate the possible health risks connected with heavy metal exposure, were calculated. It was reassuring to find that both EDI and THQ values were below the acceptable thresholds, suggesting that the consumption of O. mykiss is not likely to pose a threat to human health. To preserve seafood safety and safeguard public health, however, constant monitoring of fish metal levels is necessary.

Urgent Response Needed: Addressing the Dengue Crisis in the Andean and Southern Cone Latin American Regions.

The dengue crisis in the Latin American region is currently intensifying, exacerbated by heavy rains, widespread flooding, and the onset of the El Niño-Southern Oscillation. The indirect consequences of the COVID-19 pandemic, which weakened healthcare systems, have further compounded the situation. Comparing the first 15 weeks of 2023 with the same period in 2024, we observed a significant average increase of 600% in the number of new cases. This translates to a 536% rise in the composite rate per 100,000 inhabitants across all countries. Brazil experienced a staggering surge from 1,425,000 cases in the initial 15 weeks of 2023 to 5,177,989 cases in the corresponding period of 2024. Similarly, Paraguay witnessed a notable escalation, with cases soaring from 12,497 in 2023 to more than 240,000 thus far in 2024, marking an increase of more than 1,825%. Bolivia, however, witnessed a reduction in cases, though the cause remains unclear. Urgent action is imperative to address this escalating crisis. Strengthening surveillance systems, enhancing vector control programs, and implementing effective public health campaigns are critical. Immediate and coordinated action by regional governments and health authorities is essential to mitigate the growing dengue crisis and safeguard public health in the region.

Air Quality Dynamics in Sichuan Province: Sentinel-5P Data Insights (2019-2023)

This study assesses air pollution in Sichuan Province, China, from January 2019 to December 2023 using Copernicus Sentinel-5P satellite data. The analysis reveals distinct seasonal variations in levels of Carbon Monoxide (CO), Nitrogen Dioxide (NO₂), Sulfur Dioxide (SO₂), and Ozone (O₃), with urban areas experiencing higher concentrations due to industrial and vehicular emissions. CO and O₃ frequently exceeded WHO guidelines, particularly in winter and summer, indicating significant health risks. While most pollutant levels remained within safety limits, the findings highlight the importance of continuous monitoring and targeted mitigation strategies to improve air quality and safeguard public health, especially in urban environments.

Seroprevalence of IgG and IgM Antibodies against Toxoplasma gondii in Dogs in Greece.

Toxoplasmosis, caused by the protozoan Toxoplasma gondii, is a zoonotic disease that affects various animal species, including dogs, that can serve as sentinels for indirectly estimating the environmental contamination. The current study aimed to determine the seroprevalence of T. gondii IgG and IgM antibodies in dogs across different regions of Greece and assess their living area as a potential risk factor. In total, 1282 blood samples were collected from dogs in urban and rural areas of Greece, including Attica and Thessaloniki. Serum samples were tested for T. gondii-specific IgG and IgM antibodies using an indirect immunofluorescent antibody test. A chi-square test was performed to assess the association between seropositivity for T. gondii and geographical location (urban/rural). The overall T. gondii seroprevalence was 47.6%, while the seroprevalence of IgG and IgM antibodies was 34.3% and 22.2%, respectively. Dogs from rural areas exhibited a significantly higher seroprevalence (53.8%) than those from urban areas (43.9%) (p < 0.001), with the estimated odds ratio being equal to 1.49 (95% CI, 1.18 to 1.65) and the relative risk increased by 22.4%. Dogs in Greece are highly exposed to T. gondii, particularly in rural areas. Measures to prevent canine infections are necessary, and basic hygiene practices, such as hand washing after petting dogs, are required to reduce human infection risk and safeguard public health.

Impact of Environmental Conditions on Soil Geochemistry in Southern Kazakhstan

This study investigated the elemental composition of soils in Kyzylorda and Turkestan (southern Kazakhstan), an area rich in natural resources but facing potential environmental threats from industry and agriculture. The goal was to establish baseline geochemical values and assess soil contamination risks. Soil samples were collected from across the region and analyzed using ICP-MS and INAA techniques, providing a comprehensive profile of 72 elements. Statistical analysis revealed significant variations in elemental concentrations, with enrichments observed for specific elements when compared with reference values. Notably, both regions shared a core set of elements including rare earth elements (yttrium series: holmium, erbium, thulium), noble metals (gold, platinum, ruthenium, palladium), and tungsten. Enrichment patterns, however, provided distinct insights. Rare earth element enrichments likely reflect the region’s geology, while elevated radioactive elements necessitate further investigation to understand potential environmental and health risks. Enrichment of iron group elements might be linked to a combination of geological factors and anthropogenic activities like mining or industrial processes. A significantly higher number of elements exceeded background levels in Kyzylorda compared with Turkestan, suggesting greater element accumulation in Kyzylorda’s soil. This difference could be attributed to variations in regional geology or historical anthropogenic activities. The established geochemical baseline for 72 elements and the identified areas of potential contamination will inform land management practices, guide future environmental monitoring efforts, and ultimately contribute to the safeguarding of public health in southern Kazakhstan.

The Impact of COVID-19 Vaccine Controversy on Parents' Perceptions of Routine Vaccinations.

Background The COVID-19 pandemic has significantly influenced public perceptions and behaviors related to vaccination. Understanding parental attitudes, knowledge gaps, and vaccination practices post-pandemic is crucial for informing effective public health strategies. This study aimed to investigate parental attitudes, knowledge, and practices toward routine childhood vaccination in the post-COVID-19 era, emphasizing shifts in perspectives and implications for vaccination strategies. Methodology A cross-sectional survey was conducted among 498 parents to assess their attitudes, knowledge, and practices regarding vaccination. Data were analyzed using descriptive statistics, chi-square tests, and t-tests where applicable, with p-values <0.05 considered statistically significant. Results The study revealed diverse parental attitudes toward vaccination post-COVID-19. While a majority (72.9%) maintained positive attitudes toward vaccination schedules and benefits, concerns regarding vaccine safety and efficacy were noted. Knowledge gaps persisted, with 16.5% strongly agreeing that children's vaccinations are weak and have no impact on disease prevention. Despite high adherence to vaccination schedules (68.9%), motivations behind vaccine administration were questioned, as 48.2% strongly disagreed that vaccination was solely for regulatory purposes. Conclusions Post-COVID-19, parental attitudes toward vaccination have evolved, reflecting increased concerns about safety and efficacy. Addressing knowledge gaps, combating misinformation, and enhancing trust in vaccination programs are imperative. Tailored communication strategies, education campaigns, and policy interventions are essential to promote vaccination acceptance and safeguard public health resilience in the post-pandemic era.

Anthrax the Most Lethal Bioterror: Synthesizing Knowledge and Insights for Researchers and Public Health Professionals

Anthrax, caused by Bacillus anthracis, poses a significant threat as both, a naturally occurring disease and a potent bioterrorism agent. This article comprehensively reviews anthrax, synthesizing historical context, biological characteristics, past bioterror incidents, and implications for public health and national security. From its ancient origins to modern-day weaponization, anthrax has been a persistent challenge. Despite advancements in diagnosis and treatment, the disease's lethal potential underscores the importance of ongoing research, surveillance, and preparedness efforts. With coordinated action among researchers, policymakers, and healthcare professionals, the global community can better mitigate the risks associated with anthrax and safeguard public health and national security.