As noted previously, timeliness and accuracy are the two of most important characteristics when we evaluate an infectious disease surveillance system. Our results show that when an infectious disease required a time-consum- ing process for diagnosis, such as the dengue fever using the previously mentioned protocol, the actual daily num- ber of infected cases and cumulative positive cases are potentially underestimated. The proposed method dynamically updates the parameters daily by making use of the most recently available information on suspect cases, and then performed estimates with a lower abso- lute relative bias than when using observed daily lab-con- firmed cases only. As shown in Table 1, the proposed ARB = c
Meningococcal diseases are of major interest for public health surveillance due to their severity and epidemic nature. Meningococcal infections are caused by the Neisseria menin- gitidis bacterium. Neisseria meningitidis is transmitted to other persons as airborne infec- tion, e.g. by couching or sneezing. Most infected do not get a disease. These persons build immunity by developing protective antibodies and become a healthy carrier (Knorr-Held and Richardson, 2003). Screening studies showed a colonisation of the mucous membranes in the rhinopharynx of more than 30%, depending on the age group, in healthy persons (Claus et al., 2005). Under certain conditions, e.g. low immunity, damage of the mucous membranes, viral infections or dry air, the bacterium can infiltrate through the mucous membranes and cause a severe and perilous disease, meningococcal meningitis, meningo- coccal sepsis or the Waterhouse-Friderichsen syndrome (Anonymous, 2005). At a macro level, the incident cases can be viewed as resulting from a sporadic component linked to the carriage, on which is superimposed from time to time a small unexpected increase in the incidence, so called hyperendemic periods (Knorr-Held and Richardson, 2003). However, Knorr-Held and Richardson (2003) base their analysis on data, where there is no person to person transmission recorded, whereas in the data, that are analysed here, clusters of cases, that were caused by person to person transmission could be found (Anonymous, 2005). There is a strong evidence that some of these hyperendemic or epidemic periods can be attributed to the influence of influenza, since they regularly occur at the end of influenza outbreaks. We will analyse the influence of influenza on meningococcal diseases based on the weekly observed number of cases of both disease types in Germany, collected in the German infectious disease surveillance system.
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There were a number of obvious limitations to this study. The temporal resolution of the data used was monthly. Internet-based surveillance systems built upon monthly data are unlikely to provide better intelligence than existing traditional surveillance systems; these com- monly rely upon weekly or daily reporting. This was a function of the availability of the notification data. Sec- ondly, the analyses were performed for a specific setting: Australia. The nuances of language will create differ- ences in the applicability, not just for different countries, but also within a country and between different settings (such as during an influenza pandemic) . Australia was selected as the study area because internet penetra- tion in Australia is very high (>80%)  and use is largely restricted to a single search engine; Google maintains a market share of over 90% in Australia . These features reduce biases associated with unequal patterns of use and/or access. Additionally, owing to its extensive size, Australia exhibits a range of climates and varying environ- mental conditions, making it susceptible to a wide range of infectious diseases, including endemic and non- endemic vector-borne diseases. Additionally, Australia has a strong public health network and comprehensive infec- tious disease surveillance systems which compile high quality data on a range of diseases. Combined, these fea- tures of internet usage and availability, infectious disease surveillance systems and diseases susceptibility patterns make Australia an ideal system in which to study the po- tential application of internet-based surveillance systems. It is hoped that this work will stimulate further research into internet-based infectious disease surveillance systems beyond Australia. Even within our own study, however, we observed variation in correlations between internet search metrics and disease notifications for the various states (Figure 2). It is imperative to develop models specific to the region of interest and to assess the performance of any internet-based system against traditional surveillance data specific to the region being monitored. Thirdly, this study analysed the performance of only single search terms in estimating infectious disease notifications. Whilst Google has not revealed the terms utilised, or the weightings applied, Google Flu Trends is reported to incorporate around 160 search terms . Despite using only a single search term for each analysis, notifications for 13 diseases
Due to the lack of hard data and the great fear of a new pandemic, contradictions emerged: scientists were uncomfortable expressing subjective estimates—which are less than scientific by their nature— and resented having to qualify their judgments, which would reveal their uncertainty. The solution to this problem suggested in The Swine Flu Affair was for policymakers to develop a series of questions and procedures to dictate a response to a newly emerging infectious disease. In Appendix E of The Swine Flu Affair, Neustadt and Fineberg propose a series of questions that they developed in response to the lessons they derived from this experience. The first question, focused on the threat to the United States, was “1. How likely is the new influenza strain to spread in the United States? What do you consider the likelihood of no outbreak, of sporadic outbreaks only, of an epidemic? Within what time[frame]?”
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This paper is motivated by spatio-temporal pattern in the occurrence of Leishmaniasis in Afghanistan and the relatively high number of zero counts. We hold the view that correlations that arise from spatial and temporal sources are inherently distinct. Our method decouples these two sources of correlations, there are at least two advantages in taking this approach. First, it circumvents the need to inverting a large correlation matrix, which is a commonly encountered problem in spatio-temporal analyses. Second, it simplifies the modelling of complex relationships such as anisotropy, which would have been extremely difficult or impossible if spatio-temporal correlations were simultaneously considered. We identify three challenges in the modelling of a spatio-temporal process: (1) accommodation of covariances that arise from spatial and temporal sources; (2) choosing the correct covariance structure and (3) extending to situations where a covariance is not the natural measure of association. Moreover, because the data covers a period that overlaps with the US invasion of Afghanistan, the high number of zero counts may be the result of no disease incidence or lapse of data collection. To resolve this issue, a model truncated at zero built on a foundation of the generalized estimating equations was proposed.
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was responsible … focused on quality assurance rather than on disease specific tests. Funding for any work related to strengthening laboratories generally comes from disease specific programs (e.g., HIV, Malaria, TB, etc.) so the laboratory work tends to focus on implementing tests with little consideration of the infrastructure that is required to assure quality practices. Disease specific programs didn’t (and for the most part, still don’t) see laboratory quality assurance and management as issues for expending their disease-specific resources. As you might imagine, this is a source of considerable frustration since the new direction for the Global Health Initiative is supposed to be focused on country ownership and sustainability. Without attention to issues of quality (including the ability of a country to procure quality test kits/reagents, access to proficiency testing, oversight of laboratories, etc.), sustainability will not be possible. With respect to diagnostic microbiology, the issues are even more complex. While many seem to think that technology will provide the answer through point-of-care assays, those are some distance off and despite supposed ‘ease of use’ those assays still require an understanding of appropriate quality assurance. In addition, many of the new molecular
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Rooted in the recognition that emerging infectious diseases occur at the interface of human, animal, and ecosystem health, the Southern African Centre for Infectious Disease Surveillance (SACIDS) initiative aims to promote a trans-sectoral approach to address better infectious disease risk management in five countries of the Southern African Development Community. Nine years after SACIDS’ inception, this study aimed to evaluate the program by applying a One Health (OH) evaluation framework developed by the Network for Evaluation of One Health (NEOH). The evaluation included a descrip- tion of the context and the initiative, illustration of the theory of change, identification of outputs and outcomes, and assessment of the One Healthness. The latter is the sum of characteristics that defines an integrated approach and includes OH thinking, OH planning, OH working, sharing infrastructure, learning infrastructure, and systemic organization. The protocols made available by NEOH were used to develop data collec- tion protocols and identify the study design. The framework relies on a mixed methods approach by combining a descriptive and qualitative assessment with a semi-quantitative evaluation (scoring). Data for the analysis were gathered during a document review, in group and individual interviews and in an online survey. Operational aspects (i.e., OH thinking, planning, and working) were found to be balanced overall with the highest score in the planning dimension, whereas the infrastructure (learning infrastructure, sys- temic organization, and sharing infrastructure) was high for the first two dimensions, but low for sharing. The OH index calculated was 0.359, and the OH ratio calculated was 1.495. The program was praised for its great innovative energy in a difficult landscape dominated by poor infrastructure and its ability to create awareness for OH and enthuse people for the concept; training of people and networking. Shortcomings were identified regarding the balance of contributions, funds and activities across member countries in the South, lack of data sharing, unequal allocation of resources, top-down management structures, and limited horizontal collaboration. Despite these challenges, SACIDS is perceived to be an effective agent in tackling infectious diseases in an integrated manner.
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Chart review identified 845 patients with a presenting diagnosis of sepsis over the specified time period. Of these patients, 792 met inclusion and exclusion criteria. There were 129 inpatient deaths in the study population. Demographics of the cohort by BMI category are sum- marized in Table 1. Six percent of study participants were morbidly obese, 24% were obese and 31% were overweight, comparable to recent national statistics . Septic patients who were underweight or morbidly obese were significantly more likely to be female. As expected, the prevalence of diabetes mellitus increased significantly with increasing BMI. There were also statistically signifi- cant differences in race across BMI categories. Length of stay (average 6.5 days) and disease severity, measured by modified APACHE II score, were not significantly associ- ated with alterations in BMI.
Non-Communicable Diseases (NCD): The Prism of diseases changed from Infectious diseases to Non Communicable disease. Non-communicable disease is a medical condition or disease that is not caused by infectious agents. It refers to chronic diseases which last for long periods of time and progress slowly. It’s a "lifestyle" disease, because the majority of these dis- eases are preventable illnesses. It has been estimated that if the primary risk factors were eliminated. Pre- ventable: 80% of heart disease stroke and type 2 Dia- betes Mellitus, 40% of cancers
[16,18,19]. Extensive insecticide spraying campaigns were directed by the National Chagas Programme and were managed by the Environmental Health Programme in the departments. The Environmental Health Programme co- ordinated with other units in the Departmental Health Office and the local PHC services (health centres), but im- plemented directly the spraying campaigns with the tech- nical direction of the National Chagas Programme. Houses were sprayed by trained community members under the supervision of municipal and/or departmental Environmental Health technicians. Of the two main vec- tors, Rhodnius prolixus was eliminated in most areas, and Triatoma dimidiata was reduced to a controllable level in western Honduras [14,20]. To maintain the risk of infec- tion at a minimum level throughout broad endemic areas, the Honduran Ministry of Health implemented a vector surveillance system consisting of vector bug reporting by the community and institutional response to the reports at local health centres.
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Ayurveda refers that the Doshas get aggravated by exogenous or endogenous causes, which further spread in body by the using improper foods and activi- ties. It vitiates Kosthagni (Metabolic enzymes) which leads to improper digestion production of Ama (toxin) and their minute Srotas (body channels) this is called Srotodushti (Disequilibrium in channels). When the Rasadhatu (plasma and lymph) containing Ama (tox- in) and aggravated Doshas, reaches the place where Kha-Vaigunya (movement tendency towards empty space) has taken place, it being unable to get into the minute channels, gets obstructed, stag- nates/accumulates there and gives rise to such diseases caused by exogenous causes. If the “Exogenous – dis- eases” get ignored then it may turn into Nija Vyadhi- “Endogenous chronic disease” and affects the immune system. Diminution of natural immunity makes the person susceptible to all infections. Therefore, Ayur- veda advocates enhancing the immunity against the diseases.
Antimicrobial Stewardship programs have been shown to be of proven benefit in curbing injudicious use of antimicrobials as institutions that employ it report marked reductions in the rates of antibiotic resistance. It consists of a multi-disciplinary approach which includes clinical microbiologists, infectious disease physicians and pharmacists. The basic operational framework of such programs relies on a heavy team approach with these category health professionals .
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The review suggests that the sentinel surveillance ap- proach is increasingly applied to NCDs since reporting of most NCDs is generally voluntary and complete case detection not required. This approach allows for the careful selection of appropriate reporting units to ensure data validity. The analysis of disease patterns and time trends of a representative population subgroup is suffi- cient as basis for health policy development and imple- mentation. Findings also indicate that primary care level is adequate for the selection of reporting units since gen- eral practitioners manage a large part of patients par- ticularly in LMICs. However, lack of EMRs, inadequate standardization and missing variables are major hin- drances at this level. Setting up sentinel networks that use a single, standardized EMR system would be a solu- tion since it increases the quantity, breadth and the timeliness of data. Furthermore, standardized data col- lection systems allow for the systematic collection of relevant information. The case sensitivity can be im- proved by applying disease detection algorithms in EMRs. However, diagnostic algorithms need to be up- dated regularly and there is no clear reference standard for the ascertainment of NCDs . Alternatively, diag- nostic guidelines can also help to ensure data quality.
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2002, this surveillance strategy has been at the forefront of guinea worm and poliomyelitis eradication efforts, and is used for responding to diseases of epidemic potential includ- ing VHFs, cholera and meningitis. The data from this sur- veillance system is amongst others entered into a district health information management system (DHIMS) for stor- age and to be used by health managers to aid them in decision-making relating to disease control and surveillance. Since March 2014, when the WHO declared the EVD outbreak , the Government of Ghana and its health sector has announced and rolled out plans to prevent and respond to any outbreak in the country. However, there have been concerns raised by various stakeholders, such as the Ghana Medical Association, that the country is not adequately prepared to handle an EVD outbreak should one occur .
In this study, we isolated and detected IBDV in seven flocks of birds. However, no clinical signs of IBDV infection were observed or reported during the study period. The weekly mortality rate and feed conversion rate in both broiler and layer flocks were within the normal range. The prevalence of IBDV in these flocks could not be determined from this study because of the small number of samples collected from each flock. The age of infected birds ranged from 7-day-old to near slaughter age in broiler birds, so it was worth considering the potential effect of IBDV infection on the occurrence of other diseases during the production cycle. Discussion with the flock owners concerning the history of previous flocks revealed that outbreaks of airsacculitis and colisepticaemia, and uneven slaughter weights had occurred. The immunosuppressive effect of subclinical IBDV infection and its significance in economic loss have been discussed by various authors (Allan et al., 1 972; Hirai et al., 1 974; Rosenberger & Gelb, 1 978). Most studies have shown that the significant economic losses due to immunosuppressive effects were mainly non-responsiveness to live attenuated respiratory vaccines (Newcastle disease and Infectious bronchitis) and subsequent outbreaks of respiratory diseases (Rosenberger & Gelb, 1 978). Fortunately, most major avian respiratory diseases are not common in New Zealand poultry flocks; in particular the country is free from Newcastle disease virus. It is therefore likely that the immunosuppressive effect of subclinical IBDV infection in NZ poultry flocks would be different from the impact reported overseas.
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Personalization in medicine is a model that allows customization of health-care to the individual person by use of genetic, proteins, personality traits, behavior, environment or other information to prevent, diagnose, and treat disease using therapy –. Personalized medicine is able to improve the safety of patients , reduce unnecessary expenses for medical procedures by providing early diagnosis and optimal therapies (e.g. for cancer, and diabetes cases) , or help avoiding adverse drug reactions . Mostly, personalized medicine yields the same outputs for the same users with the same characteristics, or for different users with the same characteristics (e.g. hyper-tailoring) . Therefore, the concept of personalization is centralized to the user’s attributes. Even though personalized medicine for cancer or diabetes started in 2005, personalized medicine for infectious diseases is first mentioned in 2016 , . This late issue of personalized for infectious disease is caused by the complexity of the predictors. Personalized medicine for cancer or diabetes is mostly researched from the genetic and risky habits, thus, the predictors in the personalization model are almost known. Whereas, a person’s risk of contracting of infectious diseases are determined by the ‘invisible’ variable: the pathogen (e.g. virus, bacteria) which the emergence only known when there are reported incidences in the area. Some of the pathogen survival depends on the availability of the reservoir (e.g. nature, land use), and the climate (e.g. weather, season). Besides that, the host (e.g. human, animal) attributes also have certain ‘role’ in infection
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Social distancing, when individuals reduce the number of social contacts they make in response to the presence of disease, is an important health-protective behaviour. Teasdale et al. (2012) used PMT to examine intentions to perform protective behaviours (including social distancing behaviour) during a hypothetical epidemic. They found that intending to stay at home during the epidemic (i.e. social distancing behaviour) was associated with all of the PMT components, with self-efficacy emerging as the single strongest predictor of intending to engage in protective behaviour during a hypothetical epidemic.
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to have fallen. However, this may not reflect a true decline in disease as there have been structural changes that could affect national surveillance over the same time period. In primary care, people seeking advice about IID can now contact NHS Direct (or NHS24 in Scotland), a 24-hour, nurse-led, telephone helpline rather than con- sult their general practitioner (GP). Clinical laboratories no longer report directly to the national centre in Eng- land but via regional units. The creation of the Health Protection Agency in 2003 reduced from 48 to nine the number of lead laboratories directly under the control of the public health services with a possible reduction in the range of microbiological tests applied to each specimen. Conversely, there have been huge advances in the meth- ods available to detect gastrointestinal pathogens, notably the introduction of molecular methods. It is therefore unclear whether the reported decline in IID is due to a genuine reduction in incidence. Answering this question is important in order to direct future food safety policy.
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that transmit their pathogens. We have therefore devel- oped a series of ontologies  that describe the anatomy of mosquitoes and ticks, mosquito insecticide resistance, as well as malaria as the first disease in this category. It was early on decided that the latter ontology, IDOMAL , would be built as an extension to IDO, the Infec- tious Disease Ontology . The first version of IDOMAL was made publicly available three years ago, at a time when IDO was still at a very early stage of devel- opment. This “wrong order” obviously led to some dis- crepancies between the two ontologies, which would have to be reconciled if IDOMAL is to be considered a bona fide extension of IDO. It is particularly important to achieve the status as early as possible, since we are in the process of developing additional ontologies in the domain of vector borne diseases such as, for example, IDODEN, a yet unpublished ontology for Dengue fever . IDODEN follows the same architecture as IDOMAL, something that proved to be extremely efficient in terms of the ontology design. We therefore decided to restruc- ture IDOMAL at this point in order to avoid major fu- ture “repair” work on several ontologies. Here, we describe both the changes introduced in IDOMAL for this purpose, as well as several other changes that have been made.
Malaria is considered one of the most significant tropical diseases of humans, being a vector borne plasmodial in- fection transmitted via the bites of the female Anopheles mosquito . According to the latest global estimates from the World Health Organization (WHO), a total of 214 million cases of malaria and 438 000 deaths oc- curred in 2015 . Significant progress has been made towards malaria control over the past decade [3–5]. As of December 2014, of the 106 countries with sustained transmission of malaria in 2000, 19 countries are in the pre-elimination or elimination phase, and seven are in the prevention of malaria reintroduction phase . To achieve the goal of elimination, a sustained and well- operated malaria surveillance system is considered as a critical measure . WHO launched Global Malaria Pro- gramme’s new initiative of 3T, Test, Treat, and Track in 2012, which supports malaria-endemic countries in their effort to achieve universal coverage with diagnostic test- ing and antimalarial treatment, as well as in strengthen- ing malaria surveillance . This program and the implementation of the 3T is contingent on the provision of timely and accurate surveillance data to monitor per- formance and identify threats to malaria control and elimination.
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