Original Article
Epidemiology
Virendra Mane; Priya Prabhu; Poorva Bhalerao
Abstract
BackgroundThe first wave of COVID-19 in India declined suddenly in September 2020 and seemed to be almost over by end of January 2021. This decline was neither predicted nor explained by any models / papers then. In their previous study, the authors had hypothesized that the cases declined due to increased ...
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BackgroundThe first wave of COVID-19 in India declined suddenly in September 2020 and seemed to be almost over by end of January 2021. This decline was neither predicted nor explained by any models / papers then. In their previous study, the authors had hypothesized that the cases declined due to increased Relative Humidity during Monsoon and had forecasted that another wave would start with dry season in February 2021 and would be contained by monsoon humidity. The present study was conducted to test the seasonality hypothesis in 2021-22. Additionally, the study also included observations about effectiveness of policy control measures on case decline.MethodsHumidity cycles in India were studied to find the most humid periods and corresponded to the change in daily cases in the country, zone-wise manner and in smaller regions. For effectiveness of policy control measures, the enforcement date and subsequent case decline (if any) were observed.ResultsDefinite association was observed between Relative Humidity and Case Decline, and Case Increase in low humidity periods. Policy controls have been found to be effective in reducing and halting case increase and causing subsequent decline.ConclusionsIn India COVID-19 shows a seasonality of increase starting the dry period around February and decline due to monsoon season. Policy controls (lockdowns) is an effective measure to arrest exponential spread of the virus. The findings may be helpful to plan control and preventive activities at local level.
Review
Clinical Epidemiology
Abdel-Hady El-Gilany
Abstract
Background: The words disease, illness and sickness are overlapping and not wholly synonymous. Illness, disease, and sickness characterize different aspects of morbidity and must be dealt with as different phenomena. Changes in one aspect may not relate to changes in another. Despite the widespread use ...
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Background: The words disease, illness and sickness are overlapping and not wholly synonymous. Illness, disease, and sickness characterize different aspects of morbidity and must be dealt with as different phenomena. Changes in one aspect may not relate to changes in another. Despite the widespread use of these terms they are utilized improperly and ambiguously making confusion in the representation of medical knowledge. These terms are improperly used by medical personnel and epidemiologists and little literature dealt with this issue. Methods: A literature search was conducted on PubMed and Google Scholar. The following search terms were used in different combination “definition,” “disease,” “illness,” “sickness,” “morbidity,” “syndrome,” “disorder,” “predisease,” and “co-morbidity”. A manual search was done in textbooks of public health, community medicine and epidemiology. The most relevant and recent literature were included in the review. Results: This short review summarizes the definition, the limitations, the overlap and the differences between disease, illness, sickness and the other related terms. Conclusion: There is a need for a measurable operational definition of disease, illness, sickness and the other related terms to be appropriate for epidemiologists and clinicians as well as applicable in both hospital and community settings.
Original Article
Epidemiology
Farshad Kakian; Arman Jobeiri; Zahra Hashemizadeh; Babak Shirazi Yeganeh; Mohammad Motamedifar
Abstract
Introduction: Bloodstream infections (BSI) cause significant morbidity and mortality worldwide. Increasing Antimicrobial drug resistance among bacterial pathogens is an important issue of concern regarding appropriate therapeutic options. The aim of this study was to provide local information of resistance ...
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Introduction: Bloodstream infections (BSI) cause significant morbidity and mortality worldwide. Increasing Antimicrobial drug resistance among bacterial pathogens is an important issue of concern regarding appropriate therapeutic options. The aim of this study was to provide local information of resistance patterns to the commonly used antibiotics in Faghihi Hospital, Shiraz, Southwest Iran.Methods: We studied the frequency and antibiogram patterns of blood culture bacterial isolates from 2018 to 2019. Antibacterial susceptibility testing was done by disk diffusion method, fulfilling the standard criteria of CLSI Performance Standards for Antimicrobial Susceptibility Testing 28th edition.Result: From the total 5935 blood cultures during the study period, 576 (9.7%) were positive. From the total positive cultures, 340 (59.1%) were gram positive and 236 (40.9%) were gram negative bacteria. S.aureus was the most common isolate (26.2%) followed by S.epidermidis (15.1%) and E.coli (14.2%). The most effective antibiotic against gram positive bacteria was vancomycin, whereas we did not find a single antibiotic choice for gram negative bacteria. E.coli isolates where most susceptible to Amikacin and P.aeruginosa isolates to Imipenem.Conclusion: Our findings suggest and emphasize the need to monitor blood cultures isolates and their susceptibility patterns yearly to observe resistance patterns affecting empirical therapy and infection control methods.
Original Article
Epidemiology
Adisu Naga Mamo; Desta Hiko Gamada; Gamachu Chemeda Feyisa; Kadir Mude Wabe
Abstract
Background: Africa accounts for 94% of malaria-related morbidity and mortality. Ethiopia is one of ten African nations that share this burden, with 60% of the population living in malaria-risk areas. Nationally, the west Arsi zone's Nensebo district is stratified as having very low transmission. However, ...
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Background: Africa accounts for 94% of malaria-related morbidity and mortality. Ethiopia is one of ten African nations that share this burden, with 60% of the population living in malaria-risk areas. Nationally, the west Arsi zone's Nensebo district is stratified as having very low transmission. However, Melka Denbi kebele reported an unfamiliar high number of malaria cases to this district during the 21st WHO week of 2021. This study aimed to investigate the magnitude and associated factors with the malaria outbreak. Methods: A descriptive study followed by an unmatched case-control study was conducted among 86 cases and 172 controls. Cases were those confirmed positive by a rapid diagnostic test (RDT) and controls were the neighborhood of cases confirmed negative by RDT. Logistic regression was computed to identify malaria contracting factors at a p-value <0.05, CI 95%. Result: Plasmodium vivax (PV) 105(52.8%) was the predominant species. Stagnant water/intermittent river within 1 km of the vicinity (AOR=4.28; 95%CI: 1.8-10.27) and staying out at night (AOR=3.94; 95%CI: 2.18-7.37) were risk factors. Screened houses (AOR=0.49; 95%CI: 0.27-0.89), good knowledge of malaria transmission (AOR=0.51; 95%CI: 0.28-0.93) and prevention and control methods (AOR=0.50; 95%CI: 0.27-0.93) were protective. Conclusion and recommendation: Illness was predominantly due to PV species known for their relapsing features. Stagnant water near homes and staying outdoors at night were risk factors. Screening houses and a good awareness of malaria reduce the risk of contracting it. Regular environmental monitoring, ensuring radical cure, and further study with a detailed entomological survey were our recommendations.
Letter to Editor
Epidemiology
Abdel-Hady El-Gilany
Abstract
This letter is concerned with the term stataphobia, which is an interesting and common among researchers of different disciplines but not well-known type of phobia. Definition, causes, effect on research productivity and how to combat stataphobia are briefly discussed. This letter is concerned with the ...
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This letter is concerned with the term stataphobia, which is an interesting and common among researchers of different disciplines but not well-known type of phobia. Definition, causes, effect on research productivity and how to combat stataphobia are briefly discussed. This letter is concerned with the term stataphobia, which is an interesting and common among researchers of different disciplines but not well-known type of phobia. Definition, causes, effect on research productivity and how to combat stataphobia are briefly discussed. This letter is concerned with the term stataphobia, which is an interesting and common among researchers of different disciplines but not well-known type of phobia. Definition, causes, effect on research productivity and how to combat stataphobia are briefly discussed. This letter is concerned with the term stataphobia, which is an interesting and common among researchers of different disciplines but not well-known type of phobia. Definition, causes, effect on research productivity and how to combat stataphobia are briefly discussed.
Original Article
HIV/AIDS
Samuel Olorunfemi Adams; Haruna Umar Yahaya; Tanimu Mohammed
Abstract
Background: The HIV/AIDS epidemic has made a nasty dent on sub-Saharan Africa’s development and has contributed to discrimination against those who live on the fringes of society or people at risk of contracting virus because of their behaviours, race, ethnicity, gender, sexual orientation or social ...
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Background: The HIV/AIDS epidemic has made a nasty dent on sub-Saharan Africa’s development and has contributed to discrimination against those who live on the fringes of society or people at risk of contracting virus because of their behaviours, race, ethnicity, gender, sexual orientation or social characteristics. Methods: Cluster Analysis techniques were implemented on cluster HIV prevalence rate in Sub- Saharan Africa so as to find out countries that could be considered same category and to investigate the concentration of the disease in respect to Socio-economic status of the country. Analysis was implemented through the general methods of Hierarchical (Agglomerative nesting) and Partitioning methods (K-Means). Relative type of validation was used for cluster validation (a mechanism for evaluating the correctness of clustering). Results: The result shows a steady increase in the prevalence of HIV/AIDs from 1990 (6.74) to 1995(9.13) after which the incidence began to decline to (2.60) in 2018. The analysis created 3 clusters from the 44 observations supplied. After clustering, Only Lesotho and Eswatini belong to the third cluster. South Africa, Zambia, Zimbabwe, Namibia, Malawi, Mozambique and Botswana belong to the second clusters which are the countries with the highest HIV/AID prevalence over the years of this study. All other countries fall in the first cluster. Conclusion: The high prevalence rate of HIV/AIDS in the sub-saharan Africa countries has created an unprecedented effect. So, understanding these variables that have influenced the path of HIV/AIDS scourge constitutes an important stake, both on the humanitarian and economic aspects due to the
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