CARTOGRAPHY AND MAPPING FOR PRECISION HEALTH: REVIEW OF ESSENTIAL ELEMENTS FOR DISEASE MAPPING

A well-developed healthcare system, decent access to clean water and sanitation, and programmes to eliminate poverty and build modern infrastructure are essential components to create healthier Malaysia's population. Non-communicable diseases currently account for most of the mortality and morbidity, although communicable diseases such as dengue fever, avian flu and covid-19 still pose a threat. The World Health Organization (WHO) identified COVID-19 is a rare pneumonia disease that originated in Wuhan, on January 12, 2020, before it became an outbreak in all countries including Malaysia. The requirement of a precise mapping and Cartography for the accurate disease mapping and data management are crucial due to a precise map gives higher resolution of the data and for more specific data analysis, interpretation and decision making process. In Malaysia, there no specific report on precise mapping for health applications, and it is therefore this paper is to identify the potential criteria and factors needed for precise health mapping applications. A precise health mapping is essential to create a precise risk map towards the surveillance and signal detection, predicting future risk, targeted interventions, and understanding disease phenomena.

Classifying Adenomyosis: Progress and Challenges

Classically, the diagnosis of adenomyosis relied on histological examination of uteri following hysterectomy and classifications focused on the depth of endometrial invasion within the myometrium. There remain uncertainties around the cut-off point for the histological diagnosis. Imaging-based diagnosis enables recognition of the condition in women not undergoing surgery and facilitates the assessment of the extent of adenomyosis within the whole uterus, as well as of affections of the uterovesical pouch and of the pouch of Douglas. In this article, we explore the diagnostic uncertainties, the need to produce a classification of the condition and the challenges towards that goal. A distinction should be drawn between disease mapping and a classification that may link histological or image-based features with clinical characteristics, or with pathophysiology. An agreed system for reporting adenomyotic lesions may enable comparisons of research studies and thus contribute towards an informed classification. To this aim, we outline the features of the condition and explore the characteristics that are considered when producing a taxonomy. These include the latest proposal for subdivision of adenomyosis into an internal and an external variant. We also explore the uncertainties linked to classifying involvement of the uterovesical pouch, the pouch of Douglas and lesions in the outer myometrium. The limitations of currently available evidence suggest that agreement on a hypothesis to underpin a classification is unlikely at present. Therefore, current efforts will probably remain focused on disease mapping.

Joint mapping of cardiovascular diseases: comparing the geographic patterns in incident acute myocardial infarction, stroke and atrial fibrillation, a Danish register-based cohort study 2014–15

Background Disease mapping aims at identifying geographic patterns in disease. This may provide a better understanding of disease aetiology and risk factors as well as enable targeted prevention and allocation of resources. Joint mapping of multiple diseases may lead to improved insights since e.g. similarities and differences between geographic patterns may reflect shared and disease-specific determinants of disease. The objective of this study was to compare the geographic patterns in incident acute myocardial infarction (AMI), stroke and atrial fibrillation (AF) using the unique, population-based Danish register data. Methods Incident AMI, stroke and AF was modelled by a multivariate Poisson model including a disease-specific random effect of municipality modelled by a multivariate conditionally autoregressive (MCAR) structure. Analyses were adjusted for age, sex and income. Results The study included 3.5 million adults contributing 6.8 million person-years. In total, 18,349 incident cases of AMI, 28,006 incident cases of stroke, and 39,040 incident cases of AF occurred. Estimated municipality-specific standardized incidence rates ranged from 0.76 to 1.35 for AMI, from 0.79 to 1.38 for stroke, and from 0.85 to 1.24 for AF. In all diseases, geographic variation with clusters of high or low risk of disease after adjustment was seen. The geographic patterns displayed overall similarities between the diseases, with stroke and AF having the strongest resemblances. The most notable difference was observed in Copenhagen (high risk of stroke and AF, low risk of AMI). AF showed the least geographic variation. Conclusion Using multiple-disease mapping, this study adds to the results of previous studies by enabling joint evaluation and comparison of the geographic patterns in AMI, stroke and AF. The simultaneous mapping of diseases displayed similarities and differences in occurrence that are non-assessable in traditional single-disease mapping studies. In addition to reflecting the fact that AF is a strong risk factor for stroke, the results suggested that AMI, stroke and AF share some, but not all environmental risk factors after accounting for age, sex and income (indicator of lifestyle and health behaviour).

The Relative Risk Estimation of Pneumonia in Malaysia using Standardized Morbidity Ratio (SMR)

Pneumonia is the most serious inflammatory disease of the respiratory system which cause millions of deaths worldwide especially for children under age five and older adults. The numbers of pneumonia cases reported keep on increasing from year to year in Malaysia. Moreover, this type of disease can become outbreak if it is not controlled. Besides using as prevention strategies for a disease risk, statistical modelling of disease mapping can also be used in monitoring as it clearly shows risk areas. The objective of this paper is to estimate the value of relative risk for pneumonia transmission by using Standardized Morbidity Ratio (SMR) method which is the conventional statistic method used in disease mapping and subsequently propose a disease risk map to show the pneumonia risk areas. Pneumonia data in Malaysia is used in estimating the relative risk. The results show that, Terengganu has the highest risk of contracting pneumonia while Pulau Pinang shows the lowest risk.