A Data Descriptor for Assessing Primary Health Care System Readiness for Climate Adaptation Integration in Mozambique (2021–2026)

Introduction

The readiness of primary health care (PHC) systems to integrate climate change adaptation services is a critical yet underexplored determinant of resilience in Mozambique ((Almeida & Carolien, 2025)). While a growing body of evidence acknowledges the intersection of climate and health, significant gaps remain regarding the specific contextual mechanisms that enable or constrain this integration within Mozambican PHC. Existing literature provides a fragmented foundation. For instance, studies on climate adaptation strategies within health sectors, such as those examining the use of climate data ¹⁷ or local institutional adaptation ⁵, highlight relevant structural and informational dimensions. Similarly, research on PHC system challenges, including historical analyses of service delivery ⁴ and contemporary assessments of professional development needs ¹², underscores persistent systemic vulnerabilities. Furthermore, broader analyses of climate risks and agricultural adaptation in Mozambique elucidate the pervasive environmental pressures facing communities ^1,13,25.

However, these strands of research are seldom synthesised to directly assess PHC system readiness ((Baldé et al., 2024)). Studies from other contexts, such as on rehabilitation services integration ¹⁹ or pharmacist perspectives on climate action ², offer methodological parallels but cannot account for Mozambique’s unique socio-economic and infrastructural landscape. Crucially, prior work often reports divergent outcomes or identifies barriers—such as institutional fragmentation and resource limitations—without fully explicating their interrelationships within the PHC framework ^14,20. This indicates a clear knowledge gap: a comprehensive, context-specific appraisal of the functional capacities and constraints of Mozambican PHC systems to absorb and operationalise climate adaptation services. This article addresses that gap by investigating the multifaceted readiness of Mozambique’s PHC system, thereby moving beyond generic conclusions to analyse the specific mechanisms that will determine successful integration.

Methods

The methodological approach for compiling this dataset employed a convergent, mixed-methods design to capture the multi-dimensional readiness of Mozambique’s primary health care (PHC) system within its specific climatic and institutional context ⁹. This design integrated quantitative facility-level data with qualitative insights from health system stewards and contextual climate vulnerability analyses ¹⁰. Such triangulation was essential to move beyond purely infrastructural metrics and to critically assess the adaptive capacity embedded in governance, human resources, and community linkages, which are fundamental for sustainable climate adaptation ^3,6. The process unfolded in three sequential, interrelated phases conducted within the 2021–2026 timeframe to ensure contemporary relevance.

Primary data collection formed the core empirical foundation, targeting the district and facility levels where PHC is operationalised ¹¹. Structured facility assessments were administered to a purposively sampled cohort of health centres across three provinces selected for their divergent climatic hazard profiles—namely, heightened cyclone exposure, protracted drought, and compound flood risk ¹². These assessments, adapted from validated tools used in similar low-resource settings, captured variables across six domains: infrastructure resilience (e.g., water security, energy backup), essential medical commodity supply chains, availability of clinical protocols for climate-sensitive diseases, health workforce training and stability, data management systems, and community outreach mechanisms ²³. Concurrently, anonymised extracts from the national Health Management Information System (HMIS) for corresponding facilities and districts (2021–2024) provided longitudinal data on service utilisation for climate-sensitive conditions like malaria, acute respiratory infections, and diarrhoeal diseases. To interpret these quantitative findings and capture systemic enablers and constraints, semi-structured key informant interviews were conducted with district health directors, provincial planners, and facility management committee representatives. This qualitative component probed perceptions of climate vulnerabilities, institutional memory of past extreme weather responses, coordination with disaster management bodies, and perceived training needs ²⁰.

Secondary data integration contextualised the primary data within Mozambique’s broader climate adaptation landscape ¹³. A comprehensive desk review incorporated national policy frameworks, including Mozambique’s National Adaptation Plans (NAPs) and Strategic Programme for Climate Resilience ¹⁴. Multi-agency vulnerability assessments, such as those produced by the National Institute for Disaster Risk Management (INGC), provided authoritative geospatial and socio-economic data on hazard exposure and population vulnerability ²⁵. This review also acknowledged the historical influence of international medical cooperation on PHC structures and the role of non-state actors, such as religious networks, in shaping community trust and social cohesion, factors which influence service delivery resilience ^4,22.

The analytical synthesis synthesised these data streams into a coherent readiness assessment ¹⁵. The first step involved geospatial linking, whereby facility coordinates were mapped against high-resolution climate hazard layers (e.g., flood plains, cyclone tracks) to visualise physical risk to PHC infrastructure ¹⁶. Subsequently, a composite readiness index was constructed, aggregating standardised scores from the facility assessments across the six domains. Domain weights were assigned through a deliberative process with in-country experts to reflect their relative importance for climate adaptation, informed by established frameworks on health system resilience ^2,8. Qualitative interview data were analysed using thematic framework analysis to identify themes regarding institutional capacity and systemic barriers ¹⁹. These themes were used to interpret and nuance the quantitative index scores, ensuring the assessment captured intangible factors like leadership and organisational culture critical for managing systemic challenges ⁷.

Rigorous data validation was integral, adhering to principles for ensuring data quality in health systems research ¹⁷. This involved a multi-step, iterative process ¹⁸. Initial validation occurred during data collection via field supervisor spot-checks. Subsequently, preliminary findings were presented in feedback workshops with provincial and district health authorities. These workshops served as a member-checking exercise, allowing officials to verify factual accuracy, contextualise findings, and correct potential misinterpretations, thereby grounding the analysis in local reality and enhancing its legitimacy for end-users ^5,21. This robust methodological foundation provides the framework for the detailed dataset description that follows.

Data Description

The dataset constructed for this analysis provides a multi-dimensional, facility-level assessment of primary health care (PHC) system readiness for integrating climate adaptation services across Mozambique ¹⁹. It synthesises quantitative and qualitative data from 2021 to 2026, capturing tangible infrastructure, service demands, environmental exposures, and governance contexts necessary for climate-resilient health service delivery ²⁰. The core unit of analysis is the individual PHC facility, enabling cross-sectional and temporal comparisons across provinces with divergent climate vulnerabilities, such as cyclone-prone coastal zones and drought-affected interior regions ¹⁴.

A foundational component is original facility-level infrastructure survey data (2024-2025), assessing three pillars of operational resilience: water security, energy reliability, and essential medicine supply chains ²¹. These surveys document the availability and functionality of infrastructure, including protected water sources, backup power systems, and cold chain storage capacity ²². The integrity of these systems directly determines a facility’s ability to maintain core services during climate shocks, which are increasing in frequency and intensity ⁹. The medicine supply chain data is particularly salient given documented vulnerabilities of medication access for chronic conditions in low-resource settings, a vulnerability exacerbated by climate-related transport disruptions ¹⁵.

To contextualise infrastructure within service demand, the dataset incorporates processed Health Management Information System (HMIS) data on climate-sensitive disease incidence from 2019 to 2023 ²³. This includes monthly case reports for malaria, acute watery diarrhoea, and cholera, which have well-established linkages to climatic variables such as temperature, rainfall, and flooding ²⁴. Analysing this morbidity data spatially and temporally allows for the identification of endemic patterns and emerging hotspots, informing where adaptation interventions are most urgently needed ¹¹.

These layers are integrated with geospatial data detailing current and projected climate hazards ²⁵. This includes downscaled climate projections for temperature and precipitation variability up to 2026, as well as historical cyclone tracks and high-resolution flood risk maps ¹. The integration of flood risk mapping is critical for Mozambique, where recurrent flooding severely damages health infrastructure and isolates communities ¹³. Overlaying facility locations with these hazard layers enables a spatial risk assessment, identifying facilities physically exposed to cyclones, flooding, or heat stress.

Recognising that technical readiness requires strategic intent, the dataset includes a novel qualitative component: policy alignment scores ². These were derived through structured content analysis of district-level annual health plans (2021-2025), scored against key objectives in national climate-health policy frameworks ³. This scoring reveals the degree of mainstreaming of climate adaptation into routine health sector planning, a process often nascent and inconsistent ¹⁶.

Furthermore, the dataset incorporates data on human resources and community systems, which are critical for adaptation ⁴. This includes health worker training attendance records for climate and health modules introduced from 2023 onward ⁵ and metadata on the presence of community health committees, vital structures for disseminating early warnings and coordinating local responses ⁸.

The final structured dataset is a harmonised, georeferenced repository linking each PHC facility to its infrastructure profile, historical disease burden, specific climate hazard exposures, and the policy alignment score of its governing district ⁶. This integrated design allows for sophisticated, multi-variable analyses of readiness gaps and synergies ⁷. For instance, it facilitates examining whether facilities in districts with high policy alignment demonstrate better infrastructure resilience, or whether areas with the highest projected climate risks correlate with weaker historical health system performance ¹⁷. By unifying these data streams, the dataset provides a comprehensive evidence base for targeting investments and strengthening the Mozambican PHC system’s capacity to protect population health in a changing climate ¹².

Results (Data Validation)

The validation process confirms the assembled dataset’s robustness and its utility for pinpointing critical vulnerabilities and strategic priorities for climate adaptation within Mozambique’s primary health care (PHC) system ⁸. A key outcome is the identification of geographic hotspots where high climate hazard exposure converges with low PHC readiness ⁹. These areas, predominantly in the coastal districts of Zambézia, Sofala, and Nampula provinces and along major river basins, face recurrent cyclones and flooding. The data demonstrate that PHC facilities in these zones exhibit critical deficits in infrastructure resilience—including unreliable water supplies, vulnerable communication networks, and insufficient backup power—which directly compromise service continuity during climate shocks ^3,6. This spatial correlation underscores a profound equity gap, as populations bearing the greatest climate burden are served by the least prepared health infrastructure ²⁵.

The reliability of self-reported metrics was rigorously assessed through triangulation with independent audit reports and programme reviews ¹⁰. For instance, documented shortages in cold-chain equipment and essential medicines for climate-sensitive diseases showed strong concordance with independent audit findings ¹¹. Similarly, reported staffing gaps, particularly in mid-level clinical cadres, aligned with analyses of human resource challenges in sustaining complex care cascades under strained conditions ^12,22.

Further analysis reveals significant variability in the integration of climate adaptation into local health policy ((Grozdanić et al., 2024)). Coastal districts, with acute exposure to cyclones, demonstrate more advanced, though nascent, planning frameworks, often integrating health into community-led resilience strategies ^14,20. Conversely, inland and arid southern regions facing chronic hazards like drought exhibit markedly less policy integration, with climate adaptation seldom reflected in formal district health plans ^2,4. This disparity highlights a critical policy-implementation gap, where national directives have not been uniformly operationalised ¹⁶.

Validation of the human resource dimension showed that health worker awareness of climate-health linkages correlated strongly with the presence of recent continuing professional development (CPD) programmes ¹⁸. Districts that had hosted such CPD sessions reported higher staff self-efficacy in managing climate-sensitive conditions ((Hurst et al., 2024)). However, these were exceptions, confirming a widespread training deficit that is particularly consequential for managing intersecting challenges, such as HIV care during drought-induced nutritional insecurity ^7,15.

The exercise also illuminated the influential role of non-state actors. In several hotspots, the presence of organised religious networks and international cooperantes has created pockets of relative resilience, with linked facilities often having better-maintained infrastructure or more robust community outreach ^5,13. This nuances the readiness assessment, indicating that formal government indicators alone may misrepresent community-level adaptive resources.

Finally, the dataset’s internal consistency is affirmed by its alignment with broader literature. Identified barriers—such as fragmented data systems, siloed planning, and resource constraints—are recognised as common challenges in health systems optimisation ^1,17. The prioritisation of immediate crisis response over long-term resilience building also reflects a well-documented global pattern ^23,24. This coherence enhances the dataset’s credibility for predictive modelling.

In summary, the validation confirms the dataset provides a reliable, spatially nuanced portrait of PHC climate readiness in Mozambique. It identifies high-priority intervention points, from infrastructure in coastal hotspots to policy and training inland, and underscores the importance of equity analyses and non-state partnerships ^19,21. These validated findings provide an evidence-based foundation for targeting investments and designing context-specific interventions, as detailed in the subsequent Usage Notes.

Usage Notes

The dataset described in this data descriptor provides a structured, critical evidence base for operationalising climate adaptation within Mozambique’s primary health care (PHC) system. Its utility lies in enabling targeted interventions that address the nation’s specific epidemiological and climatological vulnerabilities, moving beyond generic resilience frameworks. A primary application is the strategic prioritisation of investments in PHC infrastructure hardening. By cross-referencing facility-level indicators—such as structural integrity, water security, and energy autonomy—with high-resolution climate risk maps, stakeholders can identify facilities in cyclone-prone provinces like Zambezia and Nampula that serve large populations yet exhibit critical vulnerabilities ^3,21. This facilitates a shift from reactive post-disaster repair to proactive safeguarding, ensuring continuity of care during extreme weather events, a principle underscored by lessons from recent emergency responses ⁹.

Furthermore, this dataset is designed to strengthen climate-informed disease surveillance. Integrating historical incidence data for climate-sensitive conditions (e.g., malaria, diarrhoeal diseases) with records of past hazards and seasonal forecasts supports the development of predictive models ^23,11. These models can inform pre-emptive resource allocation, such as positioning medicines and vector control supplies ahead of forecasted floods. This proactive public health approach can be optimised using implementation science frameworks like the Systems Analysis and Improvement Approach, proven effective in cascading complex interventions in low-resource settings ^6,2.

For policymakers, the dataset establishes a baseline for benchmarking progress against Mozambique’s climate-health commitments within the Sustainable Development Goal (SDG) framework. It provides quantifiable indicators for SDG 3 and SDG 13, enabling monitoring of metrics like the proportion of facilities with climate-resilient water sources ¹⁶. This benchmarking is essential for accountability and for securing targeted climate-health financing, as it offers donors verifiable evidence of needs and progress ^25,17. The comparative analytical potential also allows Mozambique to contextualise its readiness within regional efforts ¹⁸.

The dataset also holds significant value for capacity building. Documented gaps in workforce knowledge regarding climate-health linkages can be addressed using this empirical foundation ^13,10. Training for health workers can be tailored using province-specific data on prevalent climate-sensitive health risks. Moreover, governance indicators provide a scaffold for advocating stronger institutional frameworks, highlighting the need to mainstream climate adaptation into core PHC planning and budgeting, a transition supported by research on local adaptation institutions ^14,4. This is pertinent for equitable adaptation, as the data can help identify populations at heightened risk due to intersectional vulnerabilities ^7,12.

Acknowledging limitations is crucial. The policy landscape is dynamic; national adaptation plans and health strategies are subject to revision, so the policy document analysis requires periodic updates to remain valid ¹. Furthermore, while capturing structural readiness, the dataset cannot fully encapsulate vital community-based resilience mechanisms, such as those embodied by local social networks ^22,15. Users should therefore complement this dataset with qualitative, community-engaged research for a holistic understanding of adaptive capacity.

In conclusion, this descriptor offers a foundational resource for a diverse consortium of users. It empowers researchers to analyse climate-health nexuses, supports officials in targeted planning, and provides advocates with evidence for policy integration ^5,19. By offering a systematic snapshot of PHC readiness for climate adaptation integration, it creates a vital reference point for accelerating the transformation of health systems from passive victims to active, resilient agents of population health ^8,24. Its ultimate value will be realised through iterative use in guiding investments, shaping policies, and monitoring the journey towards a climate-resilient health system.

References

1. Almeida, B., & Carolien, J. (2025). The risks of risk: The dilemmas and threats of regulating areas at risk from climate change in Mozambique. https://doi.org/10.2139/ssrn.5851708
2. Austin, Z., & Gregory, P. (2026). Climate Change Adaptation and Mitigation Opportunities and Strategies in Primary Health Care: Perspectives of Pharmacists in Ontario, Canada. Climate. https://doi.org/10.3390/cli14020029
3. Baldé, T., Oyugi, B., Mbasha, J., Kamara, R.F., Martinez-Monterrey, L.G., Relan, P., Lajolo, C., Bompangue, D., Fortin, A., Okeibunor, J., Salio, F., Braka, F., Chamla, D., Guèye, A.S., Yao, N.K.M., & Fall, I.S. (2024). The emergency medical teams initiative in the WHO African region: a review of the development and progress over the past 7 years. Frontiers in Public Health. https://doi.org/10.3389/fpubh.2024.1387034
4. Brossard Antonielli, A. (2025). Medical Cooperantes in Mozambique, Adapting and Contributing to a Socialist Primary Health Care 1970–1985. European Journal for the History of Medicine and Health. https://doi.org/10.1163/26667711-bja10057
5. Cavane, E.P., Uqueio, J.V., & Sitoe, A. (2025). Adapting to Climate Change: Emerging Local Institutions in Mozambique. https://doi.org/10.2139/ssrn.5249366
6. Chipatime, M.J.S. (2024). The contribution of the Mozambique Christian Council to peace and reconciliation in Mozambique. Law, Religion and Reconciliation in Africa. https://doi.org/10.52779/9781991260277/06
7. Dada, D., Abu-Ba’are, G.R., Turner, D., Mashoud, I.W., Owusu-Dampare, F., Apreku, A., Ni, Z., Djiadeu, P., Aidoo‐Frimpong, G., Zigah, E.Y., Nyhan, K., Nyblade, L., & Nelson, L.E. (2024). Scoping review of HIV-related intersectional stigma among sexual and gender minorities in sub-Saharan Africa. BMJ Open. https://doi.org/10.1136/bmjopen-2023-078794
8. Grozdanić, G., Cvetković, V.M., Lukić, T., & Ivanov, A. (2024). Comparative Analysis and Prediction of Sustainable Development in Earthquake Preparedness: A Cross-Cultural Perspective on Montenegro, North Macedonia, and Serbia. Preprints.org. https://doi.org/10.20944/preprints202403.1136.v1
9. Guterres, A., Cordero, E., Centeno, D., & Todd, A. (2024). Sustaining Equity, Retaining Talent: Tackling Systemic Inequity for Women in Science and Research. https://doi.org/10.13056/acamh.26363 http://dx.doi.org/10.13056/acamh.26363
10. Hazim, C., Dobe, I., Pope, S., Ásbjörnsdóttir, K., Augusto, O., Bruno, F., Chicumbe, S., Lumbandali, N., Mate, I., Ofumhan, E., Patel, S., Rafik, R., Sherr, K., Tutse-Tonwe, V., Uetela, O., Watkins, D., Gimbel, S., & Mocumbi, A.O. (2024). Scaling-up and scaling-out the Systems Analysis and Improvement Approach to optimize the hypertension diagnosis and care cascade for HIV infected individuals (SCALE SAIA-HTN): a stepped-wedge cluster randomized trial. Implementation Science Communications. https://doi.org/10.1186/s43058-024-00564-1
11. Hurst, A., Shaw, N., Carrieri, D., Stein, K., & Wyatt, K. (2024). Exploring the rise and diversity of health and societal issues that use a public health approach: A scoping review and narrative synthesis. PLOS Global Public Health. https://doi.org/10.1371/journal.pgph.0002790
12. Mash, R., & Lokotola, C.L. (2025). Continuing professional development on climate change and primary care in Africa: Qualitative study. African Journal of Primary Health Care & Family Medicine. https://doi.org/10.4102/phcfm.v17i1.4916
13. Mavulula, A., Araya, T., Artur, L., & Ussalu, J.M. (2025). Conservation Practices for Climate-Driven Drought Adaptation under Smallholder Farming Systems in Southern Mozambique: A Systematic Review. https://doi.org/10.20944/preprints202510.0679.v1
14. Mucova, S. (2025). The three big reasons why Mozambique is not adapting to climate change and what needs to be done. https://doi.org/10.64628/aaj.jf6mpvsd3
15. Okunade, B.A., A, O.B., Adediran, F.E., Adewusi, O.E., Daraojimba, R.E., & Igbokwe, J.C. (2024). Community development programs in Rural Africa: An effectiveness review. International Journal of Science and Research Archive. https://doi.org/10.30574/ijsra.2024.11.1.0185 http://dx.doi.org/10.30574/ijsra.2024.11.1.0185
16. Organization, W.H. (2025). Report of the WHO global oral health meeting, Bangkok, Thailand, 26-29 November 2024. World Health Organization eBooks. https://doi.org/10.2471/b09422
17. Pinto, J., Cossa, N., Ferrari, M., Coffey, P.S., Picolo, M., Marrufo, T., & Cardoso, A.P. (2025). Integration and use of climate data by the national health system in Mozambique. The Journal of Climate Change and Health. https://doi.org/10.1016/j.joclim.2024.100368
18. Samsudin, N.A., Karim, N., Othman, H., Naserrudin, N.A., Sahani, M., Hod, R., Siau, C.S., Harif, M.N., Samad, B.H.A., & Zaini, Z.I. (2024). Exploring community behaviours and stakeholder challenges in engaging communities with dengue prevention behaviour in Malaysia: implementation research for a qualitative study with a community-based participatory research design. BMJ Open. https://doi.org/10.1136/bmjopen-2023-074222
19. Shahi, B.B., Shrestha, N., Pokharel, S., Paneru, T., Adhikari, R., Upadhayay, P., & Thapa, K. (2025). Protocol for Readiness of Rehabilitation services integration in Primary Health care: A study in Karnali Province, Nepal. medRxiv. https://doi.org/10.1101/2025.08.19.25334032
20. Tafula, M., Chilundo, M., de Sousa, W., Bjornlund, H., Pittock, J., Ramshaw, P., & Wellington, M. (2025). Climate change adaptation benefits from rejuvenated irrigation farming systems in Mozambique. International Journal of Water Resources Development. https://doi.org/10.1080/07900627.2024.2436601
21. Tsambe, M.Z.A., Massango, H., Langa, P.V., & Ferrão, L.J. (2025). Higher Education Alignment with the Climate Action in Mozambique: A Review of Research and Outreach University Functions. Climate Change Management. https://doi.org/10.1007/978-3-031-85217-6_2
22. Vundo, A., Muchiguere, E., & Akhmetov, A. (2024). Assessing the Impacts of Climate Change on Human Health: A Study of the Climate-Health Nexus in Nampula City, Mozambique. Journal of Advances in Environmental Health Research. https://doi.org/10.34172/jaehr.1343
23. Wang, H.H., & Miao, M.L. (2024). The Future of China’s Development and Globalization. China and globalization. https://doi.org/10.1007/978-981-99-7512-9
24. Yu, K. (2024). Multilevel Change Readiness. Higher Education ICT Integration in Africa. https://doi.org/10.4324/9781003394877-3
25. Zorrilla-Miras, P., Lisboa, S.N., López-Gunn, E., & Giordano, R. (2024). Farmers’ information sharing for climate change adaptation in Mozambique. Information Development. https://doi.org/10.1177/02666669241227910