CURRENT ISSUE

ABSTRACT: Climate change is changing how emerging infectious diseases (EIDs) spread over the world. The ecological conditions in which diseases, vectors, and hosts interact are changing because of rising temperatures, shifting patterns of rainfall, and increasingly frequent extreme weather events. This narrative review compiles existing research on climate-sensitive infectious illnesses and elucidates the principal mechanisms influencing observed changes. Food- and water-borne illnesses (e.g., cholera, leptospirosis) are increasingly linked to droughts, floods, and disruptions in infrastructure. Vector-borne diseases like dengue, chikungunya, malaria, and Lyme disease are spreading to highland and temperate areas. At the same time, zoonotic spillovers like Ebola, Nipah, and SARS-CoV-2 are happening more commonly in areas where the ecosystem has been altered. New worries are thermotolerant fungal infections and microorganisms that live in permafrost. This review does not offer new epidemiological modelling; instead, it puts recent Global Burden of Disease (GBD) estimates into context. These estimates reveal that the burden of infectious diseases is rising in regions that are sensitive to climate change, including sub-Saharan Africa, South Asia, and Latin America. Weak surveillance systems, health disparities caused by climate change, and broken data streams are some of the biggest gaps in response. Improvements in AI-based forecasting, satellite surveillance, pathogen genomes, and One Health methods provide useful tools for taking action before something happens. It is important to build public health systems that are climate-responsive, transdisciplinary, and fair in order to reduce the growing dangers posed by infectious illnesses connected to climate change.

ABSTRACT: One of the major public health emergencies that has affected lives globally is infectious disease outbreaks. These issues are of great concern due to their potential to transcend borders. The control and management of such outbreaks even with the attention channelled towards it globally has been a difficult task in many developing and underdeveloped countries of the world of which the majority of sub-saharan african countries fall under. However, with this review, we aim to contribute to the body of knowledge dedicated towards control of infectious diseases by analyzing the preparedness of Sub-Saharan African (SSA) countries in managing infectious disease outbreaks based on lessons from recent outbreaks (with focus on COVID-19, Lassa fever and Ebola outbreaks). In carrying out this narrative review, we make use of PubMed and African Journals Online (AJOL) as the primary literature sources. To ensure we capture publications from reputable organizations that are solely involved in control of infectious diseases in the region, we carried out a grey literature search.
However in this review, we synthesized challenges such as weak healthcare systems, inadequate healthcare infrastructure, inefficient surveillance systems, poor data management and reporting practices, limited laboratory capacity and reliance on external donors for supplies during emergencies.
The review proposes potential interventional measures aimed at addressing these challenges aimed at enhancing the preparedness
The findings from this review provide critical insights into the preparedness gaps and potential interventions, informing policy and practice to enhance the region's resilience future outbreaks.

ABSTRACT: For centuries, health was viewed from the lens of biomedicine as the core. This view considered medical professionals and hospitals as the sole agents and venues where health could be obtained, with only passive mentions of the impact of social determinants of health. In a paradigm shift from this view in 1978, at the Alma-Ata Declaration in Kazakhstan, 134 member countries of the WHO formalized the recognition of the social determinants of health into a global policy. Factors such as accessibility, affordability, availability, social and economic status, and education about health services are crucial for population health. The Alma-Ata Declaration required the governments of member countries to include deliberate policies that strengthen and promote population health, by ensuring that social measures are included in their national development plans while recognizing the rights of collective and individual participation of their populations. The phrase “Primary Health Care” (PHC) was then adopted. It was defined as “essential health care based on practical, scientifically sound and socially acceptable methods which are of relevant technology, made accessible and affordable to families and communities through their participation”. Health became a human right underpinned by equity and population participation principles. The aftermath of the Declaration was an immediate implementation challenge. It was soon to be realized that PHC interventions are not linear and generalizable like biomedical interventions which have specific measures and predictable outcomes. To date, there is no blueprint for universal intervention measures because economic disparities, social and situational contexts differ and determine the success of any intervention measure. Our review explores the challenges and successes of the implementation of PHC in Kazakhstan, the birthplace of the global health policy on PHC.

ABSTRACT: The rapid application of artificial intelligence (AI) in diagnostic disciplines such as radiology, pathology, microbiology, and genomics has revolutionized the way in which doctors and laboratory workers provide patient care. AI has enhanced the efficacy, accuracy, and cost-effectiveness of laboratory operations, clinical decision support systems, and image interpretation. However, these advantages are accompanied by a severe behavioral issue: an excessive reliance on automation could result in a generation of professionals who lack the reasoning abilities necessary to independently assess or contextualize machine outputs. The dual effects of AI integration are the focus of this paper, which highlights its beneficial aspects—including decreased cognitive load, increased confidence, and educational reinforcement—as well as its adverse effects, which include skill degradation, diagnostic deskilling among trainees, complacency, and reduced situational awareness. The research emphasizes the potential for unregulated dependence on AI to progressively alter professional conduct and expertise by utilizing case examples from radiology, pathology, laboratory medicine, and clinical decision support, as well as parallels from automation in aviation. In order to address these concerns, a conceptual framework is proposed that integrates AI into a "human-in-the-loop" approach, thereby preserving the significance of human judgment while leveraging machine accuracy. In order to achieve equilibrium, strategies include curriculum reform to integrate AI with hands-on experience, regular retraining, the implementation of explainable AI to promote active thinking, and institutional measures similar to recurrent training in high-stakes sectors. Ultimately, AI should complement the existing infrastructure rather than supplant it. In order to guarantee this, we must establish strategic educational, organizational, and regulatory safeguards to preserve diagnostic expertise, ensure accountability, and maintain the resilience of healthcare systems as they become increasingly dependent on intelligent technologies.