Suzbijanje geografskog širenja zaraze: kuga u Italiji od 1347.-1851.

After the establishment of the first quarantine station in the Republic of Ragusa (modern-day Dubrovnik) in 1377, the states and principalities of Italy developed a sophisticated system of defensive quarantine in an attempt to protect themselves from the ravages of plague. Using largely unknown and unseen historical maps, this paper reconstructs the extent and operation of the system used. It is shown that a cordon sanitaire existed around the coast of Italy for several centuries, consisting of three elements: (i) an outer defensive ring of armed sailing boats in the Mediterranean and the Adriatic, (ii) a middle coastal ring of forts and observation towers, and (iii) an inner defensive ring of land-based cavalry. The principles established, although not especially successful at the time against a disease of (then) unknown aetiology, are still used today in attempts to control the spread of infections of animal and human populations.Nakon uspostave prvoga lazareta u Dubrovačkoj Republici 1377., talijanske državice i kneževine razradile su sustav karantena kako bi se zaštitile od razarajućega djelovanja kuge. Oslanjajući se mahom na dosad nepoznate povijesne karte, u ovome se članku rekonstruira kako je i u kojem razmjeru djelovao sustav zaštite. Duž talijanske obale stoljećima je postojao sanitarni kordon, a sastojao se od tri dijela: (i) vanjski pojas sastavljen od naoružanih jedrenjaka na Sredozemnom i Jadranskome moru, (ii) srednji obrambeni pojas sastavljen od utvrda i promatračnica te (iii) unutarnji obrambeni pojas na kopnu sastavljen od konjice. Premda ovaj sustav svojevremeno i nije bio pretjerano uspješan u zaštiti od bolesti (tada) nepoznate etiologije, njegova se načela još uvijek rabe za sprječavanje širenja bolesti među ljudima i životinjama

Spatial Growth Rate of Emerging SARS-CoV-2 Lineages in England, September 2020-December 2021

This paper uses a robust method of spatial epidemiological analysis to assess the spatial growth rate of multiple lineages of SARS-CoV-2 in the local authority areas of England, September 2020-December 2021. Using the genomic surveillance records of the COVID-19 Genomics UK (COG-UK) Consortium, the analysis identifies a substantial (7.6-fold) difference in the average rate of spatial growth of 37 sample lineages, from the slowest (Delta AY.4.3) to the fastest (Omicron BA.1). Spatial growth of the Omicron (B.1.1.529 and BA) variant was found to be 2.81 × faster than the Delta (B.1.617.2 and AY) variant and 3.76× faster than the Alpha (B.1.1.7 and Q) variant. In addition to AY.4.2 (a designated variant under investigation, VUI-21OCT-01), three Delta sublineages (AY.43, AY.98 and AY.120) were found to display a statistically faster rate of spatial growth than the parent lineage and would seem to merit further investigation. We suggest that the monitoring of spatial growth rates is a potentially valuable adjunct to outbreak response procedures for emerging SARS-CoV-2 variants in a defined population

Abrupt transition to heightened poliomyelitis epidemicity in England and Wales, 1947–1957, associated with a pronounced increase in the geographical rate of disease propagation

The abrupt transition to heightened poliomyelitis epidemicity in England and Wales, 1947–1957, was associated with a profound change in the spatial dynamics of the disease. Drawing on the complete record of poliomyelitis notifications in England and Wales, we use a robust method of spatial epidemiological analysis (swash-backwash model) to evaluate the geographical rate of disease propagation in successive poliomyelitis seasons, 1940–1964. Comparisons with earlier and later time periods show that the period of heightened poliomyelitis epidemicity corresponded with a sudden and pronounced increase in the spatial rate of disease propagation. This change was observed for both urban and rural areas and points to an abrupt enhancement in the propensity for the geographical spread of polioviruses. Competing theories of the epidemic emergence of poliomyelitis in England and Wales should be assessed in the light of this evidence

Spatial growth rate of emerging SARS-CoV-2 lineages in England, September 2020–December 2021

This paper uses a robust method of spatial epidemiological analysis to assess the spatial growth rate of multiple lineages of SARS-CoV-2 in the local authority areas of England, September 2020-December 2021. Using the genomic surveillance records of the COVID-19 Genomics UK (COG-UK) Consortium, the analysis identifies a substantial (7.6-fold) difference in the average rate of spatial growth of 37 sample lineages, from the slowest (Delta AY.4.3) to the fastest (Omicron BA.1). Spatial growth of the Omicron (B.1.1.529 and BA) variant was found to be 2.81× faster than the Delta (B.1.617.2 and AY) variant and 3.76× faster than the Alpha (B.1.1.7 and Q) variant. In addition to AY.4.2 (a designated variant under investigation, VUI-21OCT-01), three Delta sublineages (AY.43, AY.98 and AY.120) were found to display a statistically faster rate of spatial growth than the parent lineage and would seem to merit further investigation. We suggest that the monitoring of spatial growth rates is a potentially valuable adjunct to outbreak response procedures for emerging SARS-CoV-2 variants in a defined population

Armed conflicts have an impact on the spread of tuberculosis: the case of the Somali Regional State of Ethiopia

<p>Abstract</p> <p/> <p>A pessimistic view of the impact of armed conflicts on the control of infectious diseases has generated great interest in the role of conflicts on the global TB epidemic. Nowhere in the world is such interest more palpable than in the Horn of Africa Region, comprising Ethiopia, Somalia, Eritrea, Djibouti, Kenya and Sudan. An expanding literature has demonstrated that armed conflicts stall disease control programs through distraction of health system, interruption of patients' ability to seek health care, and the diversion of economic resources to military ends rather than health needs. Nonetheless, until very recently, no research has been done to address the impact of armed conflict on TB epidemics in the Somali Regional State (SRS) of Ethiopia.</p> <p>Methods</p> <p>This study is based on the cross-sectional data collected in 2007, utilizing structured questionnaires filled-out by a sample of 226 TB patients in the SRS of Ethiopia. Data was obtained on the delay patients experienced in receiving a diagnosis of TB, on the biomedical knowledge of TB that patients had, and the level of self-treatment by patients. The outcome variables in this study are the delay in the diagnosis of TB experienced by patients, and extent of self-treatment utilized by patients. Our main explanatory variable was place of residence, which was dichotomized as being in 'conflict zones' and in 'non-conflict zones'. Demographic data was collected for statistical control. Chi-square and Mann-Whitney tests were used on calculations of group differences. Logistic regression analysis was used to determine the association between outcome and predictor variables.</p> <p>Results</p> <p>Two hundred and twenty six TB patients were interviewed. The median delay in the diagnosis of TB was 120 days and 60 days for patients from conflict zones and from non-conflict zones, respectively. Moreover, 74% of the patients residing in conflict zones undertook self-treatment prior to their diagnosis. The corresponding proportion from non-conflict zones was 45%. Fully adjusted logistic regression analysis shows that patients from conflict zones had significantly greater odds of delay (OR = 3.06; 95% CI: 1.47-6.36) and higher self treatment utilization (OR = 3.34; 95% CI: 1.56-7.12) compared to those from non-conflict zones.</p> <p>Conclusion</p> <p>Patients from conflict zones have a longer delay in receiving a diagnosis of TB and have higher levels of self treatment utilization. This suggests that access to TB care should be improved by the expansion of user friendly directly observed therapy short-course (DOTS) in the conflict zones of the region.</p

Tracking the spatial diffusion of influenza and norovirus using telehealth data: A spatiotemporal analysis of syndromic data

Background: Telehealth systems have a large potential for informing public health authorities in an early stage of outbreaks of communicable disease. Influenza and norovirus are common viruses that cause significant respiratory and gastrointestinal disease worldwide. Data about these viruses are not routinely mapped for surveillance purposes in the UK, so the spatial diffusion of national outbreaks and epidemics is not known as such incidents occur. We aim to describe the geographical origin and diffusion of rises in fever and vomiting calls to a national telehealth system, and consider the usefulness of these findings for influenza and norovirus surveillance. Methods: Data about fever calls (5- to 14-year-old age group) and vomiting calls (≥ 5-year-old age group) in school-age children, proxies for influenza and norovirus, respectively, were extracted from the NHS Direct national telehealth database for the period June 2005 to May 2006. The SaTScan space-time permutation model was used to retrospectively detect statistically significant clusters of calls on a week-by-week basis. These syndromic results were validated against existing laboratory and clinical surveillance data. Results: We identified two distinct periods of elevated fever calls. The first originated in the North-West of England during November 2005 and spread in a south-east direction, the second began in Central England during January 2006 and moved southwards. The timing, geographical location, and age structure of these rises in fever calls were similar to a national influenza B outbreak that occurred during winter 2005–2006. We also identified significantly elevated levels of vomiting calls in South-East England during winter 2005–2006. Conclusion: Spatiotemporal analyses of telehealth data, specifically fever calls, provided a timely and unique description of the evolution of a national influenza outbreak. In a similar way the tool may be useful for tracking norovirus, although the lack of consistent comparison data makes this more difficult to assess. In interpreting these results, care must be taken to consider other infectious and non-infectious causes of fever and vomiting. The scan statistic should be considered for spatial analyses of telehealth data elsewhere and will be used to initiate prospective geographical surveillance of influenza in England.

Adolescent health in rural Ghana: A cross-sectional study on the co-occurrence of infectious diseases, malnutrition and cardio-metabolic risk factors.

In sub-Saharan Africa, infectious diseases and malnutrition constitute the main health problems in children, while adolescents and adults are increasingly facing cardio-metabolic conditions. Among adolescents as the largest population group in this region, we investigated the co-occurrence of infectious diseases, malnutrition and cardio-metabolic risk factors (CRFs), and evaluated demographic, socio-economic and medical risk factors for these entities. In a cross-sectional study among 188 adolescents in rural Ghana, malarial infection, common infectious diseases and Body Mass Index were assessed. We measured ferritin, C-reactive protein, retinol, fasting glucose and blood pressure. Socio-demographic data were documented. We analyzed the proportions (95% confidence interval, CI) and the co-occurrence of infectious diseases (malaria, other common diseases), malnutrition (underweight, stunting, iron deficiency, vitamin A deficiency [VAD]), and CRFs (overweight, obesity, impaired fasting glucose, hypertension). In logistic regression, odds ratios (OR) and 95% CIs were calculated for the associations with socio-demographic factors. In this Ghanaian population (age range, 14.4-15.5 years; males, 50%), the proportions were for infectious diseases 45% (95% CI: 38-52%), for malnutrition 50% (43-57%) and for CRFs 16% (11-21%). Infectious diseases and malnutrition frequently co-existed (28%; 21-34%). Specifically, VAD increased the odds of non-malarial infectious diseases 3-fold (95% CI: 1.03, 10.19). Overlap of CRFs with infectious diseases (6%; 2-9%) or with malnutrition (7%; 3-11%) was also present. Male gender and low socio-economic status increased the odds of infectious diseases and malnutrition, respectively. Malarial infection, chronic malnutrition and VAD remain the predominant health problems among these Ghanaian adolescents. Investigating the relationships with evolving CRFs is warranted

H5N1 and 1918 Pandemic Influenza Virus Infection Results in Early and Excessive Infiltration of Macrophages and Neutrophils in the Lungs of Mice

Fatal human respiratory disease associated with the 1918 pandemic influenza virus and potentially pandemic H5N1 viruses is characterized by severe lung pathology, including pulmonary edema and extensive inflammatory infiltrate. Here, we quantified the cellular immune response to infection in the mouse lung by flow cytometry and demonstrate that mice infected with highly pathogenic (HP) H1N1 and H5N1 influenza viruses exhibit significantly high numbers of macrophages and neutrophils in the lungs compared to mice infected with low pathogenic (LP) viruses. Mice infected with the 1918 pandemic virus and a recent H5N1 human isolate show considerable similarities in overall lung cellularity, lung immune cell sub-population composition and cellular immune temporal dynamics. Interestingly, while these similarities were observed, the HP H5N1 virus consistently elicited significantly higher levels of pro-inflammatory cytokines in whole lungs and primary human macrophages, revealing a potentially critical difference in the pathogenesis of H5N1 infections. These results together show that infection with HP influenza viruses such as H5N1 and the 1918 pandemic virus leads to a rapid cell recruitment of macrophages and neutrophils into the lungs, suggesting that these cells play a role in acute lung inflammation associated with HP influenza virus infection. In addition, primary macrophages and dendritic cells were also susceptible to 1918 and H5N1 influenza virus infection in vitro and in infected mouse lung tissue