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This case study is based on a real-life outbreak investigation undertaken in Mozambique in 1981. This case study describes and promotes one particular approach to unknown disease outbreak investigation. Investigational procedures, however, may vary depending on location and outbreak. It is anticipated that the epidemiologist investigating an unknown disease outbreak will work within the framework of a "multidisciplinary investigation team". It is through the collaborative efforts of this team, with each member playing a critical role, that outbreak investigations are successfully completed. Some aspects of the original outbreak and investigation have, however, been altered to assist in meeting the desired teaching objectives and to allow completion of the case study in less than 3 hours., Competing Interests: The authors declare no competing interest.

Network models of infectious disease epidemiology can potentially provide insight into how to tailor control strategies for specific regions, but only if the network adequately reflects the structure of the region's contact network. Typically, the network is produced by models that incorporate details about human interactions. Each detail added renders the models more complicated and more difficult to calibrate, but also more faithful to the actual contact network structure. We propose a statistical test to determine when sufficient detail has been added to the models and demonstrate its application to the models used to create a synthetic population and contact network for the USA.

The research relevance is determined by the prevalence and impact of brucellosis in the developing livestock landscape of the Republic of Kazakhstan, which requires immediate assessment to understand the current state due to dynamic changes in animal breeding technologies. The study aims to implement various diagnostic programmes and compare the data obtained with information provided by other organisations. To achieve this goal, the "gold standard" research methods were used, a set of classical serological methods, which included the Rose-Bengal test, agglutination reaction, complement binding reaction, enzyme-linked immunosorbent assay, as well as the analysis method and graph analytical method. The results showed that the most infected with brucellosis were epizootic units in Aktobe, Kostanay, Mangistau, Atyrau, Akmola and West Kazakhstan regions, with infection rates exceeding 23.4%. At the same time, Almaty, Turkestan, and Karaganda regions were the least vulnerable, with infection rates not exceeding 3.1%. The largest number of animals with brucellosis was registered in West Kazakhstan Region and the smallest - in Zhambyl Region. This is due to the peculiarities of keeping and geographical locations of the regions of Kazakhstan. Thus, we can classify the situation in Almaty, Pavlodar, Karaganda and Zhambyl regions as class A, as having a low degree of infection. Kostanay, Akmola, Kyzylorda and Atyrau regions are considered to be zones with a medium degree of infection, belonging to class B. In turn, all other regions are characterised by a high degree of infection and are assigned to class C. The practical significance of the study is due to the contribution of valuable information to the scientific understanding of the epidemiology of brucellosis in the Republic of Kazakhstan. The findings provide a basis for the development of targeted intervention strategies and policy recommendations to mitigate the impact of brucellosis on livestock. [ABSTRACT FROM AUTHOR]

In recent years, the proliferation of health data sources due to computer technologies has prompted the use of visualization techniques to tackle epidemiological challenges. However, existing reviews lack a specific focus on the spatial and temporal analysis of epidemiological data using visualization tools. This study aims to address this gap by conducting a scoping review following the PRISMA-ScR guidelines, examining the literature from 2000 to 2024 on spatial–temporal visualization techniques when applied to epidemics, across five databases: PubMed, IEEE Xplore, Scopus, Google Scholar, and ACM Digital Library until 24 January 2024. Among 1312 papers reviewed, 114 were selected, emphasizing aggregate measures, web platform tools, and geospatial data representation, particularly favoring choropleth maps and extended charts. Visualization techniques were predominantly utilized for real-time data presentation, trend analysis, and predictions. Evaluation methods, categorized into standard methodology, user experience, task efficiency, and accuracy, were observed. Although various open-access datasets were available, only a few were commonly used, mainly those related to COVID-19. This study sheds light on the current trends in visualizing epidemiological data over the past 24 years, highlighting the gaps in standardized evaluation methodologies and the limited exploration of individual epidemiological data and diseases acquired in hospitals during epidemics. [ABSTRACT FROM AUTHOR]

On December 31st 2019, Chinese Health Authorities in Wuhan city of their Hubei province, diagnosed 29 pneumonia cases of unknown etiology and informed WHO (World Health Organization). The unknown virus resembled SARS (severe acute respiratory syndrome), that occurred in China in November 2002, caused by a novel corona virus spilling over from an animal reservoir and transmitted by respiratory droplets. More than 8000 cases and 774 deaths were caused by SARS and circa US$20 billion coasted for its control.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a viral pathogen that quickly became a global pandemic in the winter of 2020-2021. In response, governments issued social distancing orders to minimize transmission by reducing community contacts. We tested the efficacy of this social distancing at the state level during the first 2 months of the pandemic in the United States. We utilized data on daily SARS-CoV-2 case numbers and human community mobility (anonymized, aggregated cell phone location data stratified into six categories used as an index of social distancing), the date of government-issued social distancing orders, demographics, urbanization and public transportation. We implemented cross-correlation to identify lag times between declines in mobility and SARS-CoV-2 cases. Incorporating state-specific lag times, we tested for associations between case counts and mobility metrics using Bayesian multilevel models. Decreased mobility around grocery stores/pharmacies, retail/recreation locations, transit stations and workplaces was correlated with decreases in SARS-CoV-2 cases with significant lag times of ≥21 days. Social distancing orders were associated with fewer cumulative SARS-CoV-2 cases when they were put in place earlier. Community mobility had already started declining prior to most social distancing orders, especially the more restrictive orders implemented later in the pandemic. Social distancing is an important tool that has been implemented throughout the pandemic to decrease SARS-CoV-2 transmission, although with significant social and economic impacts. Our results suggest that declines in cases were observed several weeks subsequent to implementation of social distancing measures, and that implementing social distancing earlier could potentially minimize the duration of time these policies need to be in effect. Our findings can inform ongoing management of this pandemic and other emerging infectious disease outbreaks by identifying areas where reductions in mobility are associated with reduced disease transmission, and the expected time frame between behavioural changes and measurable population outcomes.

Recent accounting for disease in the aftermath of the Spanish Civil War has been contained within study of hunger in the early 1940s. Historians have cited the typhus epidemic which hit Spain between 1939 and 1945 as demonstrating a causal link between widespread semi-starvation and disease. Though important, the focus on hunger risks losing sight of other vital elements in the onset and transmission of typhus, however, as well as the way the epidemic's progress sheds light on population movement as central to the broader social history of the war and its aftermath. By paying close attention to epidemiological records, this article argues that the direct causes of typhus and its vertiginous spread were primarily ideological and spatial. It shows first how the war's victors used the language of political and bacterial contagion to claim spuriously that the wartime Republic was responsible for the epidemic. It then demonstrates how the intense confinement on a huge scale of those linked to the Republic was at the root of the disease. Transmission depended on this mass imprisonment and on the increased circulation of families to support those in captivity. Finally, typhus influenced the social imagination of the Franco regime and its anxiety about hygiene, prisons, and control of the movement of the urban poor. [ABSTRACT FROM AUTHOR]

Non-alcoholic fatty liver disease (NAFLD) has rapidly become the most common liver disease globally and is currently estimated to affect 38% of the global population. Only a minority of patients with NAFLD will progress to cirrhosis or hepatocellular carcinoma, but from this vast population the total number of patients who are at risk of such severe outcomes is increasing. Worryingly, individuals are increasingly being affected by NAFLD at an earlier age, meaning there is more time for them to develop severe complications. With considerable changes in dietary composition and urbanisation, alongside the growth in obesity and type 2 diabetes in the global population, in particular in developing countries, the global proportion of persons affected by NAFLD is projected to increase further. Yet, there are large geographical discrepancies in the prevalence rates of NAFLD and its inflammatory component non-alcoholic steatohepatitis (NASH). Such differences are partly related to differing socio-economic milieus, but also to genetic predisposition. In this narrative review, we discuss recent changes in the epidemiology of NAFLD and NASH from regional and global perspectives, as well as in special populations. We also discuss the potential consequences of these changes on hepatic and extrahepatic events. [ABSTRACT FROM AUTHOR]

JUUL is a groundbreaking electronic cigarette (e-cig) and the preeminent vaping product on the market. We present an overview of the rapid and spectacular rise of JUUL and its remarkable fall within the timespan of 2015 - 2020. We highlight JUUL's entering the market in June 2015, becoming the industry leader in mid 2017, and experiencing a litany of setbacks by late 2019 through to early 2020. We address the role played by JUUL in the ongoing epidemic of youth vaping. We also feature competing views on the public health impact of JUUL use (in particular), and e-cig vaping (in general). We further highlight the latest trends in youth vaping and sales records for JUUL and tobacco cigarettes. In view of the ongoing pandemic of COVID-19, we briefly summarize the existing evidence on the relationship between vaping and smoking and the prevalence, disease course, and clinical outcomes of COVID-19.

The 2019-nCoV is officially called SARS-CoV-2 and the disease is named COVID-19. This viral epidemic in China has led to the deaths of over 1800 people, mostly elderly or those with an underlying chronic disease or immunosuppressed state. This is the third serious Coronavirus outbreak in less than 20 years, following SARS in 2002-2003 and MERS in 2012. While human strains of Coronavirus are associated with about 15% of cases of the common cold, the SARS-CoV-2 may present with varying degrees of severity, from flu-like symptoms to death. It is currently believed that this deadly Coronavirus strain originated from wild animals at the Huanan market in Wuhan, a city in Hubei province. Bats, snakes and pangolins have been cited as potential carriers based on the sequence homology of CoV isolated from these animals and the viral nucleic acids of the virus isolated from SARS-CoV-2 infected patients. Extreme quarantine measures, including sealing off large cities, closing borders and confining people to their homes, were instituted in January 2020 to prevent spread of the virus, but by that time much of the damage had been done, as human-human transmission became evident. While these quarantine measures are necessary and have prevented a historical disaster along the lines of the Spanish flu, earlier recognition and earlier implementation of quarantine measures may have been even more effective. Lessons learned from SARS resulted in faster determination of the nucleic acid sequence and a more robust quarantine strategy. However, it is clear that finding an effective antiviral and developing a vaccine are still significant challenges. The costs of the epidemic are not limited to medical aspects, as the virus has led to significant sociological, psychological and economic effects globally. Unfortunately, emergence of SARS-CoV-2 has led to numerous reports of Asians being subjected to racist behavior and hate crimes across the world.

Abstract Background Dengue has become a major public health threat in Bangladesh since 2000, when the first outbreak was reported. Each outbreak has distinct characteristics, and thus, the report of the outbreak helps to understand the disease process and subsequent clinical management of these patients. On that ground, the study was designed to sketch the clinico-epidemiological characteristics of the 2018 dengue outbreak in Bangladesh. Methods This hospital-based cross-sectional study was conducted in one of the largest public medical college hospitals and a single private hospital located in the southern and northern parts of the megacity of the country. A total of 297 confirmed dengue cases were assessed with a preformed pretested questionnaire. Clinico-epidemiological and laboratory parameters were reported along with sociodemographic details. Statistical analysis was performed with SPSS 20. Results Male patients were predominantly affected by dengue infection. The mean age of the patients was 31.24 ± 13.99 (SD) years, with a range from 2 to 85 years. Eighty-two percent of patients reported from the Dhaka metropolitan city. The highest percentage of cases (37.1%) was isolated from Bansree, Dhaka city, followed by Rampura (21.4%) and Khilgaon (6.2%). In addition to common symptoms, e.g., fever (90.6%), headache (90.6%), chills (81.8%), anorexia and vomiting (76.4%), backache, and redness of the eyes were two prominent symptoms that affected more than two-thirds of the study population. On the other hand, less common symptoms, such as cough, abdominal pain, and respiratory distress, were present in 39.7%, 33.7%, and 15.5% of patients, respectively. Overall, 17.6% of patients were hypotensive during admission, with a mean systolic blood pressure of 107.65 ± 18.17 (SD) mmHg. Other prominent signs were dehydration (80.5%) and rash (33%). Conclusion This outbreak was especially characterized by gastrointestinal symptoms, which were predominant along with other typical features.

Objective To investigate the infection source, transmission route and risk factors of clustered upper respiratory tract infection with pharyngeal pain and fever in an education center in Nanchang city, so as to provide theoretical basis and experience for the treatment of the same type of epidemic in the future. Methods On August 29, 2021,an education center in Nanchang City reported a cluster epidemic mainly characterized by pharyngeal pain and fever. Case search was conducted according to the case definition, and the cases were retrospectively analyzed to describe their three distribution and investigate suspicious factors. Pharyngeal swab samples were collected, and were detected by 42 kinds of respiratory pathogens microfluidic microchip method. Reverse transcription polymerase chain reaction was used for nucleic acid detection of the samples. Results This outbreak was transmitted by aerosol and contact. A total of 26 cases of Haemophilus influenzae infection occurred in 19 days, with a total infection rate of 6. 12%. The main clinical symptoms were pharyngeal pain and fever. A total of 17 throat swab specimens were collected, 13 of which were positive for Haemophilus influenzae nucleic acid. The epidemic had been effectively controlled through measures such as isolation and treatment of the cases, environmental disinfection and health education. Conclusion This is an outbreak caused by Haemophilus influenzae, and cutting the transmission route is the key to prevention and control. [ABSTRACT FROM AUTHOR]

Background Breakthrough infections of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are well documented. The current study estimates breakthrough incidence across pandemic waves, and evaluates predictors of breakthrough and severe breakthrough infections (defined as those requiring hospitalization). Methods In total, 89 762 participants underwent longitudinal antibody surveillance. Incidence rates were calculated using total person-days contributed. Bias-corrected and age-adjusted logistic regression determined multivariable predictors of breakthrough and severe breakthrough infection, respectively. Results The incidence was 0.45 (95% confidence interval [CI],.38–.50) during pre-Delta, 2.80 (95% CI, 2.25–3.14) during Delta, and 11.2 (95% CI, 8.80–12.95) during Omicron, per 10 000 person-days. Factors associated with elevated odds of breakthrough included Hispanic ethnicity (vs non-Hispanic white, OR = 1.243; 95% CI, 1.073–1.441), larger household size (OR = 1.251 [95% CI, 1.048–1.494] for 3–5 vs 1 and OR = 1.726 [95% CI, 1.317–2.262] for more than 5 vs 1 person), rural versus urban living (OR = 1.383; 95% CI, 1.122–1.704), receiving Pfizer or Johnson & Johnson versus Moderna, and multiple comorbidities. Of the 1700 breakthrough infections, 1665 reported on severity; 112 (6.73%) were severe. Higher body mass index, Hispanic ethnicity, vaccine type, asthma, and hypertension predicted severe breakthroughs. Conclusions Breakthrough infection was 4–25 times more common during the Omicron-dominant wave versus earlier waves. Higher burden of severe breakthrough infections was identified in subgroups. [ABSTRACT FROM AUTHOR]

This is the second part of a two-part series article. Recently, we have been in the middle of a difficult time due to the Covid-19 pandemic. Pandemics or global epidemics are not new to humankind; they have occurred many times in history. The discourse of epidemiology describes mainly the causal factors which need to be mitigated to prevent or combat the effects of epidemics. In epidemiology, we are not concerned for a person, but rather every individual globally, to make life healthier for all. In this article, we will discuss the basics of epidemiological practice that scientists have used for centuries to prevent epidemics with great results. Overall, we plan for better global health aided by epidemiology. [ABSTRACT FROM AUTHOR]

Candida auris is an emerging fungus that represents a serious health threat globally. In Italy, the first case was detected in July 2019. Then, one case was reported to the Ministry of Health (MoH) on January 2020. Nine months later, a huge number of cases were reported in northern Italy. Overall, 361 cases were detected in 17 healthcare facilities between July 2019 and December 2022 in the Liguria, Piedmont, Emilia-Romagna, and Veneto regions, including 146 (40.4%) deaths. The majority of cases (91.8%) were considered as colonised. Only one had a history of travel abroad. Microbiological data on seven isolates showed that all but one strain (85.7%) were resistant to fluconazole. All the environmental samples tested negative. Weekly screening of contacts was performed by the healthcare facilities. Infection prevention and control (IPC) measures were applied locally. The MoH nominated a National Reference Laboratory to characterise C. auris isolates and store the strains. In 2021, Italy posted two messages through the Epidemic Intelligence Information System (EPIS) to inform on the cases. On February 2022, a rapid risk assessment indicated a high risk for further spread within Italy, but a low risk of spread to other countries. [ABSTRACT FROM AUTHOR]

In recent years, the proliferation of health data sources due to computer technologies has prompted the use of visualization techniques to tackle epidemiological challenges. However, existing reviews lack a specific focus on the spatial and temporal analysis of epidemiological data using visualization tools. This study aims to address this gap by conducting a scoping review following the PRISMA-ScR guidelines, examining the literature from 2000 to 2024 on spatial–temporal visualization techniques when applied to epidemics, across five databases: PubMed, IEEE Xplore, Scopus, Google Scholar, and ACM Digital Library until 24 January 2024. Among 1312 papers reviewed, 114 were selected, emphasizing aggregate measures, web platform tools, and geospatial data representation, particularly favoring choropleth maps and extended charts. Visualization techniques were predominantly utilized for real-time data presentation, trend analysis, and predictions. Evaluation methods, categorized into standard methodology, user experience, task efficiency, and accuracy, were observed. Although various open-access datasets were available, only a few were commonly used, mainly those related to COVID-19. This study sheds light on the current trends in visualizing epidemiological data over the past 24 years, highlighting the gaps in standardized evaluation methodologies and the limited exploration of individual epidemiological data and diseases acquired in hospitals during epidemics.

Vaccine development, in most cases, is a long, complex process, often lasting years and involving a combination of public and private stakeholders. Particularly, the vaccine clinical development process is highly regulated by several guidelines, regulatory pathways and science-based recommendations from experts. Designing and executing a successful clinical development plan for any candidate vaccine requires a solid scientific, medical, operational and regulatory knowledge and expertise, to comply with regulations and assure adequate benefit-risk balance for the product to be used in mass vaccination of healthy populations.The purpose of this study was to assess the approaches and practices related to Clinical Development functions, and related activities among vaccine manufacturers based in emerging countries, and to identify industry needs in terms of organizational development and training needs. A structured questionnaire designed specifically for assessing indicators of clinical activities, in the last five years, comprised of four sections aimed to collect information on (1) the organizational structure and the activities conducted by the clinical functions; (2) the clinical trial design ability and the management of clinical trial documents; (3) the clinical trial management and monitoring activities; (4) the quality aspects of clinical activities. The results suggest that the great majority of respondents is engaged in intense clinical development activities, as indicated by the high number of licensed vaccines available and supplied in the national markets or in foreign markets, including vaccines with WHO prequalification status.Areas to further strengthen the clinical activities and medical research preparedness were identified. Greater engagements of stakeholders’ and investments will be required to expand the clinical basis in vaccine R&D, and to support achieving a high level of preparedness in emerging countries, for development of new vaccines against future regional epidemics and global pandemics.

Simple Summary: We describe results from a panel study in which pigs from a 17-sow African swine fever (ASF) positive herd in Thái Bình province, Vietnam, were followed over time to record the date of onset of ASF signs and the date of death from ASF. Our objectives were to (1) fit a susceptible-exposed-infectious-removed disease model to the data with transmission coefficients estimated using approximate Bayesian computation; (2) provide commentary on how a model of this type might be used to provide decision support for disease control authorities. Detailed datasets of epidemics afflicting smallholder herds are rare. This study provides insight into how ASF progresses in a small-scale semi-intensive pig herd in Vietnam and generated a dataset that facilitated the use of a modeling approach to describe the transmission dynamics in this frequently underreported sector. We describe results from a panel study in which pigs from a 17-sow African swine fever (ASF) positive herd in Thái Bình province, Vietnam, were followed over time to record the date of onset of ASF signs and the date of death from ASF. Our objectives were to (1) fit a susceptible-exposed-infectious-removed disease model to the data with transmission coefficients estimated using approximate Bayesian computation; (2) provide commentary on how a model of this type might be used to provide decision support for disease control authorities. For the outbreak in this herd, the median of the average latent period was 10 days (95% HPD (highest posterior density interval): 2 to 19 days), and the median of the average duration of infectiousness was 3 days (95% HPD: 2 to 4 days). The estimated median for the transmission coefficient was 3.3 (95% HPD: 0.4 to 8.9) infectious contacts per ASF-infectious pig per day. The estimated median for the basic reproductive number, R0, was 10 (95% HPD: 1.1 to 30). Our estimates of the basic reproductive number R0 were greater than estimates of R0 for ASF reported previously. The results presented in this study may be used to estimate the number of pigs expected to be showing clinical signs at a given number of days following an estimated incursion date. This will allow sample size calculations, with or without adjustment to account for less than perfect sensitivity of clinical examination, to be used to determine the appropriate number of pigs to examine to detect at least one with the disease. A second use of the results of this study would be to inform the equation-based within-herd spread components of stochastic agent-based and hybrid simulation models of ASF. [ABSTRACT FROM AUTHOR]

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Background: Dengue has become a major public health threat in Bangladesh since 2000, when the first outbreak was reported. Each outbreak has distinct characteristics, and thus, the report of the outbreak helps to understand the disease process and subsequent clinical management of these patients. On that ground, the study was designed to sketch the clinico-epidemiological characteristics of the 2018 dengue outbreak in Bangladesh. Methods: This hospital-based cross-sectional study was conducted in one of the largest public medical college hospitals and a single private hospital located in the southern and northern parts of the megacity of the country. A total of 297 confirmed dengue cases were assessed with a preformed pretested questionnaire. Clinico-epidemiological and laboratory parameters were reported along with sociodemographic details. Statistical analysis was performed with SPSS 20. Results: Male patients were predominantly affected by dengue infection. The mean age of the patients was 31.24 ± 13.99 (SD) years, with a range from 2 to 85 years. Eighty-two percent of patients reported from the Dhaka metropolitan city. The highest percentage of cases (37.1%) was isolated from Bansree, Dhaka city, followed by Rampura (21.4%) and Khilgaon (6.2%). In addition to common symptoms, e.g., fever (90.6%), headache (90.6%), chills (81.8%), anorexia and vomiting (76.4%), backache, and redness of the eyes were two prominent symptoms that affected more than two-thirds of the study population. On the other hand, less common symptoms, such as cough, abdominal pain, and respiratory distress, were present in 39.7%, 33.7%, and 15.5% of patients, respectively. Overall, 17.6% of patients were hypotensive during admission, with a mean systolic blood pressure of 107.65 ± 18.17 (SD) mmHg. Other prominent signs were dehydration (80.5%) and rash (33%). Conclusion: This outbreak was especially characterized by gastrointestinal symptoms, which were predominant along with other typical features. [ABSTRACT FROM AUTHOR]

Background and Objectives: Given the importance of the early detection of any outbreak or change in the trend of meningitis, this study was conducted to estimate the fixed and dynamic alarm threshold levels of meningitis and its outbreak in Iran. Materials and Methods: In this study, the data of all patients from 20¬ March 2016 to 20 March 2019 were extracted from the National Meningitis Disease Surveillance System. Alarm threshold levels were calculated separately for different seasons and provinces. To determine the alarm threshold levels, four methods of Upper Control Limit (UCL), relative increase, statistical cut off points, and recommendations provided by the World Health Organization were used. Results: The alarm threshold levels for confirmed cases were determined for Iran according to the upper limits of cumulative sum (CUSUM) algorithm and the statistical cut off points based on the 90th percentile, 2 cases per day for Iran. The fixed amount was 3 to 5 cases per week in populations under 30,000 and 5 to 7 per week in populations between 30,000 and 100,000. According to the relative increase method, a 30% increase in one week compared to previous weeks was considered as the threshold level. Conclusion: The use of alarm threshold levels reported in this study can be a basis for detecting meningitis outbreaks.

Background: Coronavirus Disease 2019 (COVID-19) is a paramount public health issue. The true statistics about COVID-19 in Egypt are veiled. Aim: To determine the incidence rate of moderate and severe SARS-CoV-2 infection among the patients seeking admission to Zagazig University Hospitals (ZUH), Egypt based on the chest Computed Tomography (CT) COVID-19 Reporting and Data System (CO-RADS) radiological criteria. Methods: All patients aged = 18 years old seeking admission to ZUH between January 1st and March 31st, 2021, were eligible for enrollment in the study if they performed non-enhanced chest CT. Assessment of clinical, laboratory, and chest CT CO-RADS radiological criteria for each patient was carried out. The patients were defined to have moderate or severe COVID-19 if they met CO-RADS 4 or 5 radiological criteria, respectively, in association with the clinical and/or laboratory criteria. Results: A total of 5549 subjects were enrolled in the study. The total number of moderate and severe COVID-19 cases diagnosed at ZUH during January 2021 was 434/1827 with a monthly incidence rate of 23.75; 95% CI (21.9-25.8) per 100.000 of the population. The total number of moderate and severe COVID-19 cases during February 2021 was 215/1622 with a monthly incidence rate of 13.25; 95% CI (11.7-15). During March, the total number of moderate and severe COVID-19 cases was 416/2100 with a monthly incidence rate of 19.8; 95% CI (18.2-21.6). Conclusion: The incidence rate of moderate and severe COVID-19 infection at ZUH is in parallel with the national COVID-19 incidence reports. [ABSTRACT FROM AUTHOR]

It is evident that all the countries surrounding Ghana have experienced epidemics of key arboviruses of medical importance, such as the recent dengue fever epidemic in Burkina Faso. Therefore, Ghana is considered a ripe zone for epidemics of arboviruses, mainly dengue. Surprisingly, Ghana never experienced the propounded deadly dengue epidemic. Indeed, it is mysterious because the mosquito vectors capable of transmitting the dengue virus, such as Aedes aegypti, were identified in Ghana through entomological investigations. Additionally, cases may be missed, as the diagnostic and surveillance capacities of the country are weak. Therefore, we review the arbovirus situation and outline probable reasons for the epidemic mystery in the country. Most of the recorded cases of arbovirus infections were usually investigated via serology by detecting IgM and IgG immunoglobulins in clinical samples, which is indicative of prior exposure but not an active case. This led to the identification of yellow fever virus and dengue virus as the main circulating arboviruses among the Ghanaian population. However, major yellow fever epidemics were reported for over a decade. It is important to note that the reviewed arboviruses were not frequently detected in the vectors. The data highlight the necessity of strengthening the diagnostics and the need for continuous arbovirus and vector surveillance to provide an early warning system for future arbovirus epidemics. [ABSTRACT FROM AUTHOR]

Resumen: Objetivo: Analizar la evolución de la epidemia de COVID-19 después del estado de alarma e identificar factores asociados a las diferencias entre las comunidades autónomas. Método: Estudio ecológico que utilizó variables epidemiológicas, demográficas, ambientales y sobre la estructura de los servicios sanitarios como variables explicativas. El periodo de análisis fue desde el 15 de marzo (inicio del estado de alarma) hasta el 22 de abril de 2020. Las tasas de incidencia y de mortalidad fueron las variables respuesta principales. La magnitud de las asociaciones se ha estimado mediante el coeficiente de correlación de Spearman y el análisis de regresión múltiple. Resultados: Las tasas de incidencia y de mortalidad en el momento del decreto del estado de alarma se asocian con las tasas de incidencia, mortalidad y demanda hospitalaria actuales. Las temperaturas medias más altas se asocian significativamente con una menor incidencia actual de COVID-19. Asimismo, una mayor proporción de personas mayores en residencias se asocia significativamente a una mortalidad actual más elevada. Conclusión: Es posible predecir la evolución de la epidemia a través del análisis de la incidencia y de la mortalidad. Las temperaturas más bajas y la elevada proporción de personas mayores en residencias son factores asociados a un peor pronóstico. Estos parámetros deben ser considerados en las decisiones sobre el momento y la intensidad de la implantación de las medidas de contención. En este sentido, fortalecer la vigilancia epidemiológica es esencial para mejorar las predicciones. Abstract: Objective: Analyze the evolution of the epidemic of COVID-19 after the alarm state and identify factors associated with the differences between the autonomous communities. Method: Ecological study that used epidemiological, demographic, environmental and variables on the structure of health services as explanatory variables. The analysis period was from March 15th (the start of the alarm state) until April 22nd, 2020. Incidence and mortality rates were the main response variables. The magnitude of the associations has been estimated using the Spearman correlation coefficient and multiple regression analysis. Results: Incidence and mortality rates at the time of decree of alarm status are associated with current incidence, mortality and hospital demand rates. Higher mean temperatures are significantly associated with a lower current incidence of COVID-19 in the autonomous communities. Likewise, a higher proportion of older people in nursing homes is significantly associated with a higher current mortality in the autonomous communities. Conclusion: It is possible to predict the evolution of the epidemic through the analysis of incidence and mortality. Lower temperatures and the proportion of older people in residences are factors associated with a worse prognosis. These parameters must be considered in decisions about the timing and intensity of the implementation of containment measures. In this sense, strengthening epidemiological surveillance is essential to improve predictions.

Botryosphaeria dothidea causes severe disease of apple trees in China. The process of conidium germination, colonization, and infection of apple fruit and branches was examined on 'Fuji' apple and the effect of temperature, surface wetness and relative humidity (RH), and host surface washates on these processes was studied in controlled environments. Initial germ tube development and hyphal growth resulted in the colonization of the host surface without forming an infection structure. Hyphae expanded radially across the host surface and, after entering lenticels, developed into a dense mycelium mass or differentiated pseudoparenchyma. Hyphae from the bottom of the pseudoparenchyma either directly penetrated the lenticel surface intercellularly through the cell layer, or formed an undifferentiated hypha that invaded the lenticel through cracks formed during the lenticel development. Conidial germination and hyphal colonization occurred at 10 to 40°C, with an optimum of approximately 28°C. Conidial germination required an RH > 95% or surface wetness but, for hyphal colonization, an RH > 90% was sufficient. Conidia germinated and formed germ tubes within 1 h under optimum conditions. However, the pathogen required a longer period at RH > 90% or surface wetness for hyphae to colonize and form pseudoparenchyma or dense mycelia on the host surface. Hyphal colonization is a crucial stage for infection of apple tissues by B. dothidea. [ABSTRACT FROM AUTHOR]